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date: 22 September 2023

Information and Civil Unrest in Dictatorshipsfree

Information and Civil Unrest in Dictatorshipsfree

  • Elizabeth Ann SteinElizabeth Ann SteinElizabeth Ann Stein is an assistant professor of Political Science at the Institute for Social and Political Studies at the State University of Rio de Janeiro, Brazil. She currently is the SGIS-National Endowment for Democracy Mark Helmke Post-doctoral Fellow at Indiana University. Her current research focuses on media freedom and presidential accountability in Latin American democracies and information, new communication technologies and anti-government mobilization in dictatorships.

Summary

Considering incidents that make headline news internationally, given the modern information and communication technology revolution, the facility of citizens to rapidly mobilize represents a considerable threat to autocratic survival. While the speed with which popular movements emerge has increased exponentially, and the news of their existence spreads faster and farther, civil unrest has threatened the stability and survival of dictators for centuries. The paranoia and machinations of dictators depicted in films, such as the portrayal of Ugandan dictator Idi Amin in The Last King of Scotland, while sensationalized, capture the astounding array of threats with which unelected leaders must concern themselves. On the one hand, they must worry about insider threats to their standing, such as conspiratorial plots from people within the dictator’s own circle or mutiny among government soldiers. On the other hand, dictators also must monitor threats originating from non-regime actors, such as new alliances forming among once-fragmented opposition groups or the possibility of sustained insurgency or a popular revolution. From force to finesse, autocratic leaders have developed a broad and evolving range of tactics and tools to diminish both internal and external domestic threats to their reign. The success of dictators’ endeavors to insulate their regimes from forces that might challenge them depends on accurate and reliable information, a resource that can be as valuable to the leader as would a large armory and loyal soldiers. Dictators invest significant resources (monetary as well as human capital) to try to gather useful information about their existing and potential opponents, while also trying to control and shape information emitted by the regime before it reaches the public. New information and communication technologies (ICTs), which have drawn a great deal of scholarly attention since the beginning of the 21st century—present both risks and rewards for dictators; inversely they also create new opportunities and hazards for citizens who might utilize them to mobilize people opposed to the regime. While civil unrest could encompass the full range of domestic, nonmilitary actors, there also needs to be a specific focus on various forms of mass mobilization. Historically, more dictators have been forced from office by elite-initiated overthrows via coups d’état than have fallen to revolution or fled amid street protests. Civil unrest, in its many forms, can affect autocratic survival or precipitate regime breakdown. While mass-based revolutions have been a relatively rare phenomenon to date, the actions of many 21st-century dictators indicate that they increasingly concern themselves with the threats posed by popular protests and fear its potential for triggering broader antigovernment campaigns. The ease of access to information (or the lack thereof) help explain interactions between authoritarian regimes and citizens emphasizes. The role of information in popular antigovernment mobilization has evolved and changed how dictators gather and utilize information to prevent or counter civil unrest that might jeopardize their own survival as well as that of the regime.

Subjects

  • Contentious Politics and Political Violence
  • Governance/Political Change
  • Political Communication

Introduction

While mass-based revolutions have been a relatively rare phenomenon to date, the actions of many 21st-century dictators indicate that they increasingly fear threats posed by popular protest and their potential for triggering broader antigovernment campaigns. Based on incidents that make international headline news, the facility of rapid popular mobilization using new information and communication technologies (ICTs) represents a considerable threat to autocratic survival.1 High quality information and fluid communication are requisite for autocratic leaders, dissidents, and the masses to deter, instigate, and participate in civil unrest, respectively. In addition, the emergence and diffusion of new ICTs have influenced the relationship between information and collective action in dictatorships.

The potential of new ICTs to facilitate the mobilization of citizens has attracted a great deal of news coverage and scholarly attention following the Arab Spring of 2010‒2011, a series of contentious mass actions that occurred in rapid succession across countries in North Africa and the Arabian peninsula that led to the fall of long-standing dictators and the regimes in Tunisia, Egypt, and Libya, and threatened other authoritarian leaders as well. ICTs present both risks and rewards for dictators; conversely they also create new opportunities and introduce potential hazards for citizens who might utilize them to become informed, express dissatisfaction, or to mobilize opposition to the regime. While the speed with which popular movements emerge has increased exponentially, and the news of their existence spreads faster and farther, civil unrest has threatened the stability and survival of dictators for centuries.

The paranoia and machinations of dictators depicted in films, such as the portrayal of former Ugandan dictator Idi Amin in The Last King of Scotland (Morgan et al., 2006), while fictionalized, capture the astounding array of threats with which unelected leaders concern themselves. On the one hand, dictators worry about insider threats to their standing, such as conspiratorial plots from people within the dictator’s inner circle or mutiny among government soldiers. On the other hand, dictators must monitor threats originating from non-regime actors, such as the formation of new alliances among once-fragmented opposition groups, or the emergence or resurgence of insurgent movements, which could lead to popular revolution or a sustained civil war. From force to finesse, autocratic leaders have developed a broad and evolving range of tools and tactics to gather, shape, and distribute information to diminish internal and external domestic threats to their reign.

Despite impediments to free and independent media in dictatorships, citizens still require information to make informed decisions about whether to support or oppose the regime and, in either case, whether to do so actively and publicly. While some citizens may get caught up in the moment and take to the streets spontaneously, the dominant assumption in the literature on mass mobilization in authoritarian regimes presumes that people act rationally, weighing the expected costs against the potential benefits before participating in an antigovernment mass action. Studies of citizens and dissidents as rational actors proceed to focus on how individuals arrive at that assessment given considerable constraints on access to reliable information.

The secrecy surrounding authoritarian governments masks the strength and disposition of the regime. Therefore, anticipating how the regime would or could respond were it to face public displays of dissent remains ambiguous for those trying to initiate antigovernment campaigns. Operating under the belief that most individuals avoid particularly risk actions, dissident leaders seek ways to assess the regime’s will and capacity for repression in order to strategize when to stage anti-regime actions and how to maximize participation in antigovernment mass actions. Further complicating matters, in repressive environments citizens rarely express dissenting opinions publicly—a process known as preference falsification—and may not even speak openly among friends and family (Kuran, 1991, 1995; Ginkel & Smith, 1999). Due to the prevalence of preference falsification among the masses, everyone from the dictator to opposition organizers to citizens themselves faces a difficult task in evaluating the breadth and depth of support for the regime.

Additionally, citizens contemplating joining the opposition not only need to gauge the probability of the opposition actions succeeding but also the degree of uncertainty over who would govern were the dictator to fall. Even if people believe that opposition to the regime pervades society, before carrying out or joining collective actions, dissident leaders and members of the public must consider whether or not they believe that widespread dissatisfaction and disapproval of the regime would translate into active participation in public anti-regime actions. Accordingly, opposition leaders must rely on various forms of direct and indirect information in planning and publicizing anti-regime mass actions. Recent events suggest that new ICTs potentially alleviate this burden and help activist leaders and their supporters overcome collective action and coordination problems. ICTs might have greater implications for civil unrest in dictatorships, where information often is scarce.

The terminology “civil unrest” encompasses the full range of domestic antigovernment actions, including some coups d’état, civil war, secessionist movements, insurgencies, and mass demonstrations. Protests and popular rebellions, that rely on the mobilization of ordinary citizens, likely benefit to a greater degree than other types of civil unrest from technologies that facilitate the exchange of information among larger groups with looser social networks. Surprisingly few studies on rebellion explicitly address how information influences collective action (Ritter & Trechsel, 2014). Just as dissidents have to do under authoritarian rule, students of collective action must “read between the lines” of these studies to figure out how information travels and what influence it has.

Studies that employ formal models of rebellion in dictatorships—a prevalent approach in this research area—are one exception; they frequently take into account the effect of information on actors’ choices, particularly whether players have equal or asymmetrical access to information about one another.2 However, even in these studies that explicitly mention information, they infrequently discuss the specific nature of the information needed and often gloss over how people obtain it. Only recently, have more researchers placed emphasis on empirically testing causal relationships between information or information technology and mass mobilization in dictatorships.

In the section that follows, I highlight how dictators control, gather, and utilize information to prevent or counter civil unrest that might jeopardize their own survival and that of the regime. In the second section, I focus on the role of dissident leaders in organizing and attracting participation in antigovernment mass actions in the context of limited information under authoritarian rule. In the third section, I turn to citizens and elaborate on how the masses obtain information, form opinions about the regime, and decide whether and when to participate in antigovernment collective actions. In each section, I address repression as a form of communication, the unique role elections play in communication in competitive authoritarian regimes, and I reflect on changes that have occurred—or that scholars anticipate will occur—with the emergence and diffusion of the Internet and other ICTs. I then conclude, offering suggestions for the direction of future research in this area.

Dictators’ Control and Gathering of Information

Dictators who attempt to insulate their regimes from forces that might challenge them count on obtaining accurate and reliable information—a resource that can be as valuable to the leader as would a large armory and loyal soldiers. Dictators invest significant resources (monetary as well as human capital) gathering information about their existing and potential opponents, while also trying to control and shape information emitted by the regime before it reaches the public (Guriev & Treisman, 2015). Since authoritarian leaders do not benefit from procedural legitimacy granted to them via free and fair elections, they derive their legitimacy through alternative mechanisms—such as the divine right of some monarchs, co-optation, or based on the regime’s economic and political performance (Frantz & Stein, 2012, 2016). Regimes must foster and protect the perception of good performance. To sustain their legitimacy,

every regime must garner popular support to continue its rule and that popular support can be built or destroyed through mass persuasion or “propaganda.” Governments traditionally maintain power by means of promulgating an ideology or by means of performance-based legitimacy. Most governments use a combination of the two approaches to maintain political stability.

(Brady, 2012, p. 7)

Absent political legitimacy, authoritarian rulers must command their position via the (potential) use of force, a more costly and less secure option.

One way through which authoritarian regimes try to obtain or sustain popular support is through direct control or manipulation of the news media. Although people strongly associate censorship with dictatorships and press freedom with democracy, recent studies cast doubt on the strength of the relationship between regime type and press freedom. Several authors suggest circumstances in which autocrats benefit from allowing relatively free and independent media (Egorov et al., 2009; Whitten-Woodring, 2009; Lorentzen, 2014), and other authors demonstrate conditions that motivate some democratic leaders to take actions to limit media freedom (Whitten-Woodring, 2009; Kellam & Stein, 2015; VonDoepp & Young, 2015). One reason this matters is that recent research has indicated that the interaction between media independence and regime type can have paradoxical effects on protest and repression; with autocracies that have independent media experiencing less protest activity than those without watchdog journalism (Whitten-Woodring & James, 2012).

In discussing levels or constraints on media freedom, I refer to the degree to which journalists and editors can report free from government interference and without fear of reprisal for their coverage, in line with a liberal view of what constitutes media freedom.3 Table 1 contrasts average press freedom, as measured by Freedom House’s annual Press Freedom Index (PFI)4 for democratic versus authoritarian regimes, controlling for economic development as measured by GDP per capita adjusted for purchasing power parity.5 Freedom House’s press freedom index evaluates political, economic, and legal obstacles to media freedom and is measured on a 100-point scale that I reverse so that higher numbers now indicate environments with greater press freedom and lower numbers indicate environments with more constraints on that freedom. I control for development because on average more poor countries are autocratic and poorer autocracies may have lower levels of state capacity than wealthier dictatorships, which could preclude the option of employing strategic censorship as the Chinese government has done (see Lorentzen, 2014). Data on regime type for this and subsequent tables come from Autocracies of the World6 and code a country as autocratic in a given year if one of the following four conditions is not met:

1.

A civilian government (as opposed to military or royal court) provides the main source of policymaking.

2.

Political leaders form multiple and competitive parties, and the parties interact and run the government through a legislature.

3.

The executive is institutionally constrained or checked by other parts of the government.

4.

Elections are used to select the political leadership, and they are largely open, competitive, and free and fair (Magaloni et al., 2013, p. 6)

Table 1 Average Press Freedom Index (reversed) by Regime Type and GDP/capita ppp (1993‒2014)

1***

2***

3***

4***

5***

6***

7***

All***

$0–$1,000

$1,001–$5,000

$5,001–$10,000

$10,001‒$20,000

$20,001‒$30,000

$30,001–$40,000

>$40,000

Total

Democracies

41.4

56.7

57.9

64.5

77.2

81.1

86.9

66.7

(59)

(428)

(338)

(377)

(211)

(253)

(183)

(1,849)

Autocracies

32.8

33.3

36.8

30.4

19.5

17.2

32.0

32.7

(135)

(704)

(271)

(242)

(36)

(30)

(124)

(1,542)

Joint Average

35.5

46.0

52.2

54.2

70.6

75.9

63.2

54.0

(194)

(1,281)

(706)

(742)

(319)

(296)

(342)

(3,880)

Note. The Press Freedom Index refers to Freedom House’s composite measure of legal, political, and economic restrictions on press freedom, reversed so that zero indicates a complete absence of press freedom and 100 indicates no restrictions placed on press freedom. For this and subsequent tables and graphs, GDP per capita adjusted for purchasing power parity come from World Bank Development Indicators (data downloaded in April 2016). Regime type is based on the Autocracies of the World Data Set’s (Magaloni et al., 2013) “demo_r” variable, which indicates whether the regime that governed the plurality of days in a given year was either democratic or authoritarian, regardless of particular institutional designs, which I have updated for 2013 and 2014. Number of country-years appears in parentheses below average value of Freedom House’s Press Freedom Index.

*** Pr(|T| > |t|) ≤ 0.001;

**Pr(|T| > |t|) ≤ 0.05;

*Pr(|T| > |t|) ≤ 0.01.

Two-sample t-tests with unequal variances of the means of press freedom between democracies and autocracies are statistically significant for every income category.

Across levels of development, press freedom suffers more, on average, in autocratic regimes than it does in democracies. The differences in the mean press freedom index for autocracies versus democracies at each level of development are statistically significant based on two-way t-tests, supporting the assumption that information flows less freely in dictatorships, regardless of development.

Censorship and Propaganda

To stave off mass rebellion, leaders focus their efforts on eliminating independent criticism that might spread dissent, while also currying favorable coverage that helps build popular support for the regime and its policies (Geddes & Zaller, 1989). Different types of dictatorship have different objectives in mind for controlling information. Totalitarian regimes seek monopoly control over mass communication to mobilize the citizenry behind the totalitarian ideology, be it fascist or communist (Linz, 2000). Personalist and monarchic authoritarian regimes may use the media and propaganda to construct a cult of personality around the leader or royal family, whereas military regimes likely focus on eliminating negative coverage that could threaten regime stability.

In Nazi Germany, Adolf Hitler and his propaganda minister Joseph Goebbels designed the massive propaganda machine with the objective to sell Nazi ideology to the German public, as if it were a brand (O’Shaughnessy, 2009). Other totalitarian regimes, such as the communist governments of Lenin’s Soviet Union and Mao’s China, relied on the careful regulation of information and government propaganda to develop new cultural identities and mobilize the masses behind that identity. In order to achieve this degree of control over messaging, Vladimir Lenin eliminated media competition within the first year of seizing power (Kenez, 1985).

In contrast, bureaucratic authoritarian regimes in South America wanted to depoliticize citizens and encourage mass complacency (O’Donnell, 1978). Bureaucratic authoritarian regimes dominated in the Southern Cone region of Latin America during the 1960s through 1980s. Led by professionalized militaries, they brought in technocrats, often trained abroad, to promote economic development directed at reducing these countries’ economic dependence on commodity exports and imported manufactured goods. To carry out these policies, which involved tactics that hurt the popular sector, the bureaucratic authoritarian governments’ primary objectives were to build public support for regime policies and thwart anti-regime collective actions (Remmer & Merkx, 1982). To do so, the regimes censored the media to ensure content that would prime citizens to evaluate the regimes based on their successes rather than their antidemocratic behaviors (e.g., triumphs over communist insurgencies vs. government responsibility for human rights violations) (Stein, 2013). Each country’s bureaucratic authoritarian regime employed different strategies for controlling publicly available information. Whereas Chile primarily relied on massive intimidation and the resulting self-censorship (Rosenberg, 1987), Brazil implemented systematic and formalized media censorship, issuing daily prohibitions to all media outlets and reserving the more punitive tactic of prior censorship for the opposition press (Marconi, 1980; Kushnir, 2004).

Intra-Elite Communication

Via censorship, repression, and a tight inner circle, dictators enshrine their regimes with secrecy in an effort to maintain an advantage over the opposition and potential rivals among the elite (Boix & Svolik, 2013). While government secrecy may create some opportunities for the leader, who is the most knowledgeable about his government, it also creates obstacles to cooperation, even between the leader and the group of elites who support him. According to several studies on dictatorships, the lack of reliable information and the asymmetrical distribution of it impede dictators’ ability to make credible commitments. These authors suggest that regimes adopt a variety of pseudo-democratic institutions, from semiautonomous legislatures to multiparty elections, to ensure that autocrats will not renege on their power- and resource-sharing commitments (e.g., Magaloni, 2008; Gehlbach & Keefer, 2011; Boix & Svolik, 2013). By formally ceding decision-making authority to other elite actors and offering paths for career advancement, the leader’s assertion gains credibility.

Institutionalization of authoritarian regimes also alters the strategies that authoritarian leaders employ against the opposition. Specifically, adopting institutions such as legislatures, political parties, and elections helps authoritarian leaders co-opt and negotiate with members of the opposition (Gandhi & Przeworski, 2006). However, incorporating these institutions simultaneously opens space for potentially public and destabilizing political contention (Frantz & Kendall-Taylor, 2014). While institutions may stave off most elite-driven transitions, regimes must employ other measures to curtail bottom-up efforts to pressure the regime for concessions or force regime change. Many authoritarian regimes utilize repression as a communicative tool to dissuade the masses from joining rebellions.

Repression as a Communicative Tool

Most research on collective action rests on the assumption that repression deters individual participation by signaling its high cost and thus impedes collective action. Repression, when coercive and observable carries with it a message that the regime will not tolerate dissent (Earl, 2003). Employing repression, while potentially persuasive in deterring participation in the short term, carries with it high costs for the regime. Apart from the direct costs, such as paying censors and soldiers, the outright use of physical repression may cost the regime its legitimacy internationally and domestically. A less obvious cost of repression stems from how it affects public expression and, in turn, the quality of information regimes can gather on their popular support, which they need to better anticipate and appease or suppress dissenters (Bratton & van de Walle, 1997). Repression likely leads citizens to self-censor their publicly shared opinions or to falsify their preferences. Ronald Wintrobe’s economic model of dictatorship describes the difficulty regimes have in gauging their true level of public support as the “Dictator’s Dilemma,” which Wintrobe suggests leads most dictators to employ both repression and co-optation (1998).

In the end, misinformed leaders frequently take actions that prove tremendously costly to them. For example, authors have attributed abrupt revolutions that bring down leaders and regimes to events that trigger some citizens to end preference falsification, which produces a bandwagon of protesters as more people express their true preferences (e.g., Iran in 1979 [Rasler, 1996], Eastern Europe in 1989 [Kuran, 1991; Lohmann, 1994], Tunisia in 2010 [Goodwin, 2011; Hussain & Howard, 2013]), and surprising defeats at the polls, as in the case of Chilean General Augusto Pinochet’s loss in the 1988 plebiscite and the forced departure of leaders of Eastern Europe and former Soviet states in the wake of post-electoral protests (e.g., Vladimír Mečiar’s government in Slovakia in 1998, Georgia’s then-President Eduard Shevardnadze in 2003, and Viktor Yanukovych in Ukraine in 2004‒2005) (Tucker, 2007; Bunce & Wolchik, 2010). In search of more enlightening data, dictators have turned to a number of counterintuitive mechanisms to elicit information, including elections, freedom of expression, and even permitting protests.

Elections as Information in Authoritarian Regimes

Elections in authoritarian regimes serve as more than just a credible commitment to share power with other elites.7 Many scholars attribute their adoption to the veneer of democracy that they offer a regime that might need to curry favor internationally (Calingaert, 2006; Hyde, 2011). Elections also allow the dictator to communicate publicly the strength of his support or at least his capacity to mobilize “supporters” to deter would-be challengers from plotting coups or discourage opposition groups from staging uprisings (Geddes, 2006; Howard & Roessler, 2006; Blaydes, 2011; Malesky & Shuler, 2011). Authoritarian elections represent one of many mechanisms that dictators adopt to gain information about popular discontent and identify opposition supporters. However, dictators face a trade-off between gathering good information, in which case they need to permit more fair elections that offer the opposition the possible chance of victory, and maintaining greater control over electoral outcomes, in which case dictators sacrifice some of the informational value of competitive elections (Malesky & Shuler, 2011). As Andreas Schedler notes, incumbents “want to bring opposition parties into the game but they also wish to keep them under control. After all, they are not interested in institutionalizing democracy, but in legitimizing their continuity in power” (2002, p. 114).

While some scholars argue that elections facilitate opposition coordination of mass actions via formalized political parties (Magaloni, 2010), others have suggested that such tactics help sustain the regime by dividing the opposition (Haugbølle & Cavatorta, 2011). Where the formal rules allow some contention, they encourage a portion of the opposition to play by the rules and push for change from within; alternatively, more radical opposition forces reject participation in authoritarian elections, preferring to express dissent through collective action or antigovernment violence.

Even fraudulent elections can prove informative. In noncompetitive elections, regimes invite election observers and subsequently engage in fraud to fulfill observers’ expectations and demonstrate their strength, while also lowering the cost of committing higher levels of fraud if necessary (Little, 2012). In multiparty elections, the regime can evaluate whether they needed to employ higher than expected efforts to manipulate the outcome. However, the use of fraud to ensure electoral victories has proven costly for many reigning incumbents because elections arguably help mobilize the opposition and activate latent participants (Tucker, 2007), which I discuss in greater detail in the subsequent section.

Other Information Tools

Beyond holding elections, some authoritarian regimes also have employed other counterintuitive information-gathering devises, such as permitting moderate levels of popular protest (Lorentzen, 2013) and allowing (adequate) freedom of the press (Egorov et al., 2009; Stockmann & Gallagher, 2011; Lorentzen, 2014). Protests can serve as “burglar alarms,”8 notifying the regime of growing dissent, allowing it to target particular groups with ameliorative actions to avert broadscale anti-regime campaigns. In addition to lending legitimacy to the regime, promoting media freedom and independence allows for investigative journalism that can help the regime monitor lower-level government officials who might engage in corruption (Egorov et al., 2009; Stockmann & Gallagher, 2011). Thus media freedom helps authoritarian rulers to improve governance and, in turn, reduce popular dissatisfaction. Just as staging elections generates information for the regime, permitting controlled protest, allowing freedom of the press, and easing restrictions on online expression also can inform authoritarian rulers about the nature of its opposition. Using data from content analyses of online discussion boards that captured user commentary prior to government censorship, Gary King and his coauthors show that the Chinese government permits selective criticism of the regime online, but quickly erases any comments that could help mobilize protests (King et al., 2013).

One should note that many of these studies on permissive freedoms of the press, expression, and assembly (e.g., Stockmann & Gallagher, 2011; King et al., 2013; Lorentzen, 2013, 2014) focus on China, a country with greater state capacity than most other regimes. Just as the literature on authoritarian elections highlights the risk of actual defeat (e.g., Howard & Roessler, 2006; Bunce & Wolchik, 2010), authoritarian governments that permit protests and free media also elevate the risk of generating common knowledge about the extent of popular dissatisfaction that could spiral quickly toward broader revolutionary action. Some authors have suggested that even in China, increasing space for online expression ultimately has empowered the country’s netizens and decreased the government’s ability to set the agenda (Esarey & Qiang, 2011). These informational devices might prove more costly than beneficial for authoritarian regimes that do not have the capacity to regulate them or shut them down should they grow increasingly contentious. The subject merits further empirical exploration across authoritarian regimes. State capacity also likely influences dictators’ approach to investing or not in ICT infrastructure, as well.

Dictatorship in the Information Age

In light of events from post-election protests in Ukraine, Moldova, and Iran to the massive mobilizations in Tunisia, Egypt, and other Middle Eastern and North African countries, the potential outcomes of expanded Internet access, either via computers or mobile phones, have attracted attention from governments, media, and scholars alike. Early research on the Internet in authoritarian regimes (e.g., Kalathil 2003; Kalathil & Boas 2003) illustrated that authoritarian regimes embraced a broad range of approaches to ICT adoption. Some countries, including Cuba, North Korea, and Burma, kept a strong grip on controlling access, investing little, and permitting only government insiders and some academics to have access to the World Wide Web (Kalathil 2003). Other countries, such as China and Egypt, invested considerably in providing Internet access to citizens, though China also invested in developing controls on Internet content, developing what has become known as China’s Great Firewall (MacKinnon, 2011).

More recent research on ICT access and use suggests that dictators face a double-edged sword: they must decide if they should accept the risk of ICTs (e.g., increased protest and information sharing), for the expected economic rewards (e.g., economic growth). Espen Geelmuyden Rød and Nils Weidmann note that “the Internet is not imposed on a particular country from the outside; rather its introduction relies critically on the permission and support of the domestic government” (2015, p. 4).

Since the commercialization of the Internet in the late 1990s, the Internet has become increasingly integrated into the world economy. To thrive economically, countries that lack natural resource wealth, require a wired society. Studies have shown that countries with better connected societies—those with higher Internet penetration rates (the number of users per 100 people)—enjoy higher economic growth, on average (Milner, 2006; Vu, 2011).9 Authoritarian leaders who govern during economic decline or stagnation—like their democratic counterparts—suffer from lowered rates of public approval. Thus, if they fear investing in ICT infrastructure due to the threats these technologies may pose, they also put their economic performance in jeopardy. For dictators, constraining the expansion of ICT access could potentially lead to a loss of performance legitimacy.

Table 2 Average Number of Internet Users per 100 People by Regime Type and GDP/capita ppp (1995–2014)

1*

2**

3

4***

5**

6***

7***

All***

$0–$1,000

$1,001–$5,000

$5,001–$10,000

$10,001–$20,000

$20,001–$30,000

$30,001–$40,000

>$40,000

Total

Democracies

1.1

4.5

10.7

22.7

39.5

41.6

66.3

25.0

(48)

(375)

(291)

(356)

(189)

(230)

(177)

(1,666)

Autocracies

0.6

3.4

10.4

15.5

30.7

14.0

34.8

10.1

(112)

(583)

(229)

(225)

(35)

(25)

(118)

(1,327)

Joint Average

0.8

4.4

10.9

21.2

37.8

40.5

53.8

19.0

(160)

(958)

(520)

(581)

(224)

(255)

(295)

(2,993)

Note. Internet users per 100 and GDP per capita ppp are from the World Bank World Development Indicators (accessed in April 2016). Regime type comes from Autocracies of the World, “demo_r” variable (Magaloni et al., 2013), which I have updated for 2013 and 2014. Number of country-years appears in parentheses below average value of Internet penetration.

*** Pr(|T| > |t|) ≤ 0.001;

** Pr(|T| > |t|) ≤ 0.05;

* Pr(|T| > |t|) ≤ 0.01.

Two-sample t-tests with unequal variances of the means of Internet penetration between democracies and autocracies are statistically significant for all income categories except group 3.

Data suggest that dictators and their regimes prefer to err on the side of fewer protests, instead taking risks with regard to economic performance. This falls in line with literature that suggests that some dictators have short time horizons and highly discount future gains (Wright 2008b). Table 2 compares data on average Internet penetration rates between autocracies and democracies for the period between 1995 and 2014; on average, authoritarian regimes had lower Internet penetration rates than did similarly developed democratic regimes, across all income categories.10 Figures 1‒7 illustrate the difference in how Internet access has expanded over time in democracies versus autocracies given a countries average per capita income. On average authoritarian regimes delayed investing in the Internet; although at higher levels of development—where democracies have reached near-universal access—autocratic regimes have narrowed this gap in recent years. In my estimation, many of these regimes have shifted their strategies from trying to limit access to the Internet toward focusing on restricting available content. While these summary data do not establish a direct causal path from dictators’ calculus of the risk versus reward of investing in ICT infrastructure, the data align with prior studies that suggest that Internet penetration rates are endogenous to regimes, with authoritarian regimes resisting expansion more so than democracies (Milner, 2006).

Figures 1–7. The growth of Internet access in democracies versus autocracies, 1995–2014, controlling for income categories.

Note. As in Table 2, Internet Access (Internet users per 100) and income categories (based on GDP per capitappp) rely on data from the World Bank World Development Indicators (accessed in April 2016). Regime type comes from Autocracies of the World, “demo_r” variable (Magaloni et al., 2013), which I have updated for 2013 and 2014. The lines in these graphs are derived via lowess smoothing and fill in gaps for missing data.

Wealthier authoritarian regimes and those with high state capacities not only seem better able to tolerate the risk of expanding Internet access, but they also can capitalize on informative benefits for the regime. Some authoritarian states use the Internet as a new apparatus for monitoring citizens and identifying dissenters. In the Middle East and North Africa, for example, countries like Saudi Arabia and the United Arab Emirates that have high-tech, well-financed tools for monitoring information technologies and sanctioning online dissent better withstood contentious episodes associated with the Arab Spring relative to countries such as Egypt and Jordan that tolerated (or were unable to limit) online dissent (Hussain & Howard, 2013).

Following on Georgy Egorov and his coauthors’ work (2009) that suggests that authoritarian states without oil permit media freedom to help monitor officials and improve good governance, I broke down average Internet penetration rates for authoritarian regimes, comparing countries that derive more than one-fifth of their GDP from oil rents. Table 3 supports the idea that petro states are less permissive with Internet access than those that may rely on them to improve principal‒agent problems. Again, controlling for income groups, for all but one income category, which has very few observations, petro states have lower average Internet penetration rates than do countries that derive a smaller percentage of their GDP from oil rents. An alternative explanation that might account for lower ICT penetration rates in petro states aligns with Joseph Wright’s (2008a) explanation for why non-oil-dependent authoritarian regimes more likely adopt legislatures; because they are “more dependent on the production of the domestic economy to generate the revenue necessary to sustain their rule, they have an incentive to establish governing institutions that constrain their own power” (Wright, 2008a, p. 322). This logic could carry over to explain why non-oil-dependent states look more favorably upon Internet access than petro states, which I define as any states that derive 20% or more of their GDP from oil rents; the Internet has the potential to serve as a constraining agent.

Table 3 Average Internet Users per 100 by Oil-Rich versus Not Oil-Rich Autocracies, Controlling for GDP per capita ppp (1995–2014)

1

2

3***

4**

5***

6

7

All***

$0 –$1,000

$1,001–$5,000

$5,001–$10,000

$10,001–$20,000

$20,001–$30,000

$30,001–$40,000

>$40,000

Total

Petrol States

2.20

4.75

12.31

15.82

16.94

34.11

17.4

≥ 20% of GDP from oil rents

(0)a

(57)

15

(90)

(17)

(20)

(70)

(239)

Other States

0.54

3.31

10.69

17.62

50.25

36.00

8.5

≥ 20% of GDP from oil rents

(107)

(490)

(192)

(122)

(16)

(0)

(45)

(972)

All Autocracies

0.61

3.45

10.86

15.99

30.68

14.01

35.36

10.4

(112)

(583)

(229)

(225)

(35)

(25)

(118)

(1,327)

Note. The percentage of GDP derived oil rents comes from the World Bank World Development Indicators (downloaded in April 2016). Note that the numbers for each income category do not total to the same number as the authoritarian regimes in Table 1. This stems from missing data for oil rents.

a Number of country-years appears in parentheses below average value of Internet penetration (World Bank World Development Indicators).

*** Pr(|T| > |t|) ≤ 0.001;

** Pr(|T| > |t|) ≤ 0.05;

*Pr(|T| > |t|) ≤ 0.01;

Cannot calculate because no cases exist in one group. Two-sample t-tests with unequal variances of the means of Internet penetration between petrol and non-petrol autocracies are statistically significant for income categories 3, 4, and 5.

Even authoritarian regimes with high state capacity or an abundance of natural resources remain imperfectly informed, particularly with regard to underlying mass support (Kuran, 1991; Ginkel & Smith, 1999), and these regimes cannot completely control information. Nevertheless, dictators generally have more and elaborates on the struggles dissident leaders face with regard to information acquisition and diffusion when mounting antigovernment campaigns.

Dissident Leaders’ Information and Communication Strategies to Overcome Collective and Coordination Problems

Leaders of the opposition require reliable information to identify potential support among the masses, the strengths and weaknesses of the regime, and opportunities for antigovernment actions. The information they acquire aids in their recruitment of participants as well as in their planning and coordination of tactics. Dissident leaders have an interest in publicly exposing the governments’ policy failures and human rights violations, while propagating the opposition’s victories to project an image of strength, which could help grow their active participant base and attract external support and resources. They must do all of this in an atmosphere in which the government restricts the free flow of information to impede exactly these efforts and citizens’ guard their opinions close to their vest, creating the Dissidents’ Dilemma. Dissident leaders therefore must rely on alternative sources to disseminate information and indirect indications of the information they seek.

Not only do dissident leaders have to obtain useful information, but in order to recruit participants they also must overcome the public’s lack of good information.11 John Ginkel and Alastair Smith acknowledge the difficulty of acquiring information in repressive regimes. “Given the limited amount of free press and other forms of information, the general public has little idea about whether the government can survive a major rebellion. Such information is costly and dangerous to obtain” (1999, p. 293). The authors highlight that dissident leaders obtain noisy information through their observations of government actions.

Organizing Protest amid Repression

Nearly all theories of mobilization based on rational actors presume that repression suppresses individuals’ willingness to participate in mass actions absent additional incentives (e.g., DeNardo, 1985; Lichbach, 1987, 1994a, 1994b; Tucker, 2007). Political opportunity theory, for example, suggests that changes in repression play a role in leaders’ decision of whether or not to hold a protest, and if one is occurring whether or not more individuals will join the protest (Opp & Roehl, 1990; Brockett, 1993, 2005; Kurzman, 1996). Activists not only consider the probability that the planned action will achieve gains but also the likelihood that anyone who chooses to participate could be arrested or beaten as a result. The logical implication is that leaders of opposition movements in authoritarian regimes must seek moments of reduced risk to attract participants. In order to do so, leaders implicitly must be able to gauge the degree of risk, presumably by monitoring government repression in other arenas, and then communicate this information to a broader audience without attracting the attention of the regime (Stein, 2016).

An extensive literature exists about the relationship of repression and protest,12 yet little consensus has emerged about the effectiveness of repression as a communicative tool for the regime in deterring protests. The breadth of hypotheses regarding the effect of repression on protest presented in this body of research runs from predicting monotonically positive or monotonically negative effects to an inverted-U pattern, or countervailing effects of higher levels of repression on the incidence of collective action. At best, one could conclude that repression affects mobilization both positively and negatively depending on the (a) intensity of repression (DeNardo, 1985; Lichbach, 1987, 1994a; Muller & Weede, 1990), (b) target of repression (Mason & Krane, 1989; Siegel, 2011), (c) timing of repression (Brockett, 2005), and (d) consistency in the application of repression versus concessions (Lichbach, 1987; Rasler, 1996). Other studies point out that findings of a positive correlation between protest and repression might be an artifact of observation (Shadmehr & Bernhardt, 2011; Ritter & Conrad, 2016). Where repression is high enough to deter protests, no protests occur (and thus no incidental repression follows). By contrast, protests might take place in countries that employ more moderate levels of protest; hence, we observe more protests and more repression.

One factor accounting for these differences stems from variations in the conceptualization and operationalization of repression, and thus what it means for a country or for protesters to experience more or higher levels of repression. Some authors focus on types of repression, distinguishing between repression targeted at individuals versus repression targeted at society (e.g., Rasler, 1996; Frantz & Kendall Taylor, 2014), while others highlight the government’s strategy of selective versus random repression (Mason & Krane, 1989). Studies distinguish between the degree of violence involved, for example, distinguishing between arrests and deaths (Khawaja, 1993), or the incident rate of repression (Francisco, 1993).

Despite the large number of studies that suggest that repressive environments invariably reduce individuals’ willingness to show up for mass actions, empirical evidence repeatedly shows that under many circumstances more repression leads to more protest or has no statistically significant relationship. These results suggest that scholars of collective action in authoritarian regimes, particularly those who employ rational choice, may need to revisit their underlying assumptions. One alternative perspective employs prospect theory, arguing that citizens are more inclined to participate in risky actions when they perceive the status quo or negotiated agreements as a loss in comparison with their objective outcome; members of the opposition who perceive government offers of accommodation as an improvement to the status quo more likely will refrain from costly actions with uncertain outcomes (Masters, 2004). This indicates that the framing of dissident causes as well as their planned mass actions could have a large effect on mass participation as well.13

Signals Sent, Signals Received

Many studies of collective action employ some form of signaling game to suggest how dissident leaders receive information about expected repression (e.g., Lohmann, 1993, 1994; Ginkel & Smith, 1999; Bueno de Mesquita, 2010). Several authors indicate that dissident leaders observe signals from government (either privately or publicly), though authors do not fully explicate (a) what type of signals they receive, (b) from where or from whom, and (c) how they receive these signals.14

Building on prior evidence that the relationship between repression and protest is less than straightforward, a few authors suggest that the role of repression in provoking protest exists because of the costly signal these actions send to latent participants. Ginkel and Smith (1999) who incorporate three players in their game—the government, dissidents (i.e., opposition leaders), and the mob—suggest that participation should grow in repressive environments. They claim that opposition leaders who initiate and participate in early antigovernment actions under the threat of repression lend credibility to their cause; the mob will more likely join movements where leaders demonstrate their degree of commitment through the high risks they accept. Ethan Bueno de Mesquita (2010) suggests that when first-actors, who he refers to as “revolutionary entrepreneurs,” engage in violent actions they likely increase mobilization, though he contends that the growth in participation results not from the power of numbers per se, but from information the entrepreneurs intentionally communicate about antigovernment sentiment to manipulate other’s beliefs about the benefits of action.

Some studies suggest that participation grows from information about actual protests that cascades through society. As the information that others protested and to what effect becomes common knowledge, it influences subsequent participation sending new information to still-latent protesters who join later protests, and so on (Kuran, 1991; Lohmann 1994, 2000). These arguments neither specify how the information reaches new members of the public nor how they become common knowledge in limited information environments.

In other research (Stein, 2016), I suggest that the missing factor from many of these arguments may be the mass media even when censored, both as the indirect provider of signals about likely repression, as well as a generator of common knowledge.15 I suggest that dissident leaders monitor media content and the government’s reaction to changes in content16 to gauge the government’s tolerance for public dissent. Empirical evidence drawn from the period of political opening (1974‒1982) during the Brazilian military dictatorship indicates that if the media challenged the regime by publishing stories on taboo subjects without suffering consequences, dissidents took this as sign that the regime was more tolerant of dissent or unable to repress it and they would subsequently initiate more mass actions. If, however, the regime responded with the suppression of content or repression of journalists in the face of media challenges, dissidents held off on initiating new mass actions, perceiving the regime’s disposition to be unfavorable toward public displays of dissent. Furthermore when this information appeared in mainstream media, it generated common knowledge about participation and consequences that influenced participation in subsequent protests.17

Dissident leaders’ ability to assess the probability of repression and its likely effects on participation and movement success represents just one school of thought about dissident leaders’ role in mobilizing the masses. Just as literature on authoritarian leaders’ behavior has adapted to evolving types of hybrid authoritarian regimes, so too has the literature on antigovernment protest in such regimes. Specifically several studies have looked at how elections, electoral fraud, and voter mobilization help opposition leaders in competitive authoritarian regimes to organize antigovernment actions.

Mobilizing Participation in Electoral Authoritarian Regimes

The distinguishing feature of competitive authoritarian regimes from other types of authoritarian regimes is that they permit some degree of real contestation with the possibility, though low, of an incumbent defeat (Howard & Roessler, 2006). While the literature on institutionalized authoritarianism highlights the benefits of pseudo-democratic institutions for authoritarian survival, the inclusion of political parties and elections inherently facilitates opposition coordination by eliminating the need to overcome obstacles to coordination present during other times, such as deciding when to protest.

Debates among the opposition about whether or not to participate in elections that the opposition and public anticipate to be less than free or fair hinge on the message the opposition’s participation would send to the regime and the outside world. Some opposition leaders see participation as a way to express their dissent (and the breadth of it among the population); while detractors see it as sending the message that the people view the incumbent regime and its institutions as legitimate. Where the opposition can overcome this hurdle and coalesce around a single candidate, Marc Howard and Philip Roessler (2006) contend that this cooperation helps mobilize people to vote against the incumbent by providing “signals to the electorate that the incumbent is vulnerable to defeat,” increasing the possibility of a “liberalizing electoral outcome” (Howard & Roessler, 2006, p. 372). Valerie Bunce and Sharon Wolchik (2010) believe that the opposition’s ability to collaborate among themselves and with civil society groups informs the regime of the degree of the threat it faces, and thus pressures the regime to make concessions about electoral procedures, voter registration, and transparent vote counts, which can improve the opposition’s chances of challenging the status quo. As the normative value placed on democracy increases, competitive authoritarian regimes have adopted an increasingly standard set of strategies to lend legitimacy to elections that includes many of the above tactics along with inviting international election monitors (Hyde 2011).

Opposition leaders are not alone in trying to mobilize participation. Regimes that incorporate competitive institutions to improve their durability also must mobilize enough of the opposition to participate in the election to appease international election monitoring organizations that procedures were fair enough for the observers to sanction the results and, thus, force the domestic opposition to accept the results. Knowing this to be the case, the presence of international election monitors actually encourages the opposition to boycott the election, sending the message to domestic and international audiences that the institutions are rigged. Because not all opposition parties willingly participate in elections that they perceive to be rigged from the start (Beaulieu & Hyde, 2009), partial boycotts, which weaken the opposition by publicly demonstrating the opposition’s disunity, occur with some frequency (Lindberg, 2006).

Many opposition groups in electoral authoritarian regimes support the presence of international election monitors believing the threat that observers might publicly allege fraud should limit the regime’s ability to renege on results in the case of an opposition victory (Kelley, 2011). Anticipating fraud, many opposition groups preemptively organize post-election protests, as was the case of the Green Movement in Iran following Ahmadinejad’s pronounced electoral victory in 2009 (Morozov, 2009b).

Opposition leaders’ ability to capitalize on events such as fraudulent elections requires them to act strategically. Part of the effectiveness of the successful Color Revolutions, a series of post-electoral protests that forced the departures of several incumbent leaders in former Soviet states, stemmed from opposition leaders’ ability to frame events in ways to attract participation of key sectors, such as youth voters (Polese & Ó’Beacháin, 2011). Once messaging is set, dissident leaders face the next challenge of reaching their audience, who increasingly may be found online.

Do Dissident Leaders Actually Lead in the New Information Age?

Prior to Facebook and Twitter and even the popularization of mobile phones, in 1994 the not-yet-known Zapatista National Liberation Army (EZLN), better known as the Zapatistas, launched an attack against the Mexican government from the southern state of Chiapas. The EZLN leader’s then-savvy use of the Internet distinguished the Zapatistas from similar insurgent movements. At the time, the majority of Internet and email use occurred through government and university networks. Subcomandante Marcos, the EZLN’s main leader—who the Mexican government believes to have been a university professor and thus would have had access to email and early online content—used the Internet to draw international attention to the indigenous community’s plight in Southern Mexico and to skirt the framing by traditional Mexican media (Schulz, 1998; Garrido & Halavais, 2003; Darling, 2008). The Zapatista leaders also used online resources to raise financial support for their campaign from sympathetic foreigners (Bob, 2005), perhaps representing one of the first incidents of crowdfunding online.

As access to the Internet in developing and non-democratic countries has grown exponentially, dissident group leaders’ perception of the utility of ICTs has evolved. Scholars claim that ICTs have two major functions: (1) they generate global awareness and (2) they mobilize domestic actors (Ritter & Trechsel, 2014; Little, 2015).

Critics of the so-called Twitter Revolutions point to the relatively low rates of diffusion of these technologies—particularly for foreign-based sites such as Twitter—among the populations in Iran, Tunisia, and Egypt (see, e.g., Morozov, 2009b; Gladwell, 2010). Other scholars challenge the quick dismissal of the importance of these technologies, highlighting the fact that those who could and did access these sites were likely “opinion leaders” (Kavanaugh et al., 2013). Andrea Kavanaugh and her coauthors contend that “opinion leaders (also called influentials) play a central role in finding and evaluating information from mass media and other sources, and sharing it actively with people in their social circles” (Kavanaugh et al., 2013, p. 4).

While people generally believe that with regard to collective action, a single person’s participation is unlikely to make the difference, under certain circumstances that might not be the case. As Timur Kuran’s behavioral cascade model suggests, depending on the underlying distribution of individuals’ threshold for participation, in some cases even small changes among a few citizens’ actions could trigger a domino-like effect. Keeping that in mind, for ICTs to affect rebellion they do not necessarily need to reach the majority of citizens. Rather, a few citizens who access them could trigger a mass rebellion if they spread the information via face-to-face communication or by becoming early participants whose actions could trigger a participatory chain reaction. The now well-known Egyptian Google executive Wael Ghonim may have been one of these influential actors when he set up a Facebook page to memorialize a murdered blogger, “We are All Khaled Said,” which served as an online arena for organizing initial protests early in the Egyptian uprising (Ritter & Trechsel, 2014). Citizen journalists and bloggers thus became the initial leaders of the early revolutionary movements (Ritter & Trechsel, 2014).

Not all Egyptians who participated personally would have accessed the Facebook page; many would have heard about it indirectly from friends or family or passed from cell phone to cell phone. The first participants in the Egyptian as well as Tunisian protests that triggered revolutions were part of the “youth bulge”—well-educated, yet unemployed and disillusioned youth—and were likely to have had higher rates of access to online social networks than subsequent participants (Howard & Hussain, 2011). The online activists may have been crucial to establishing the critical mass, after which traditional modes of mobilization took over (Ritter & Trechsel, 2014).

Furthermore, traditional media interact with and report on content in new media, amplifying the reach of independent news producers and commentators. To keep pace with technological development and commercial demands, news organizations have gone through a process of convergence in both the production and the distribution of news (García-Avilés, Kaltenbrunner, & Meier, 2014). Major media organizations often publish blogs by their columnists on the outlet’s website. Journalists who work for traditional news outlets may pick up stories from independent bloggers and social media outlets. Erin Snider and David Faris (2011) note the symbiotic relationship between a nascent independent press and online social media in promoting the events that ultimately led to the protests known as the Arab Spring.

However, do these individuals count as dissident leaders in the traditional sense? They may have initiated the spread of information, but they did not lead established interest groups, political parties, or social movements. Do the Internet and social networking tools eliminate the need for organizations and leaders? Scholars have noted that the new communications environment changes the obstacles to collective action, reducing the need for traditional organizations (Bimber et al., 2005). Furthermore, David Siegel’s (2011) work on the structure of networks and repression suggests that particular network structures that occur in online social networks (e.g., the “opinion leader” network) may help movements survive when the regime cannot quickly identify and target leaders for removal. Regardless, no mass action can succeed unless it attracts the support of a sufficient percent of the masses. In the next section I discuss the literature on information, public opinion, and political mobilization among the masses.

Citizens’ Opinion Formation and Decision-making under Authoritarian Rule

With a few exceptions, until recently elections have not been the norm in most authoritarian regimes. Generally the absence of free and fair competitive elections leaves citizens with few institutionalized ways through which they can express their opinion about those who rule over them, let alone demand leadership change. Despite their lack of electoral say, citizens still form opinions about the regime that influence other behaviors, including their desire and willingness to participate in antigovernment demonstrations or join an opposition political party. As in democracies, citizens living under dictatorship form their opinion of the regime based on the publicly available information they consume and on their own experiences and the experiences of their acquaintances. However, unlike democracies where information is a commodity that can be acquired easily with the morning news, in authoritarian regimes quality information is a scarce good in high demand. To make relatively informed choices, citizens must evaluate the accessible information while questioning its veracity knowing that the government may have censored sources purposefully to mislead the public.

Michael Chwe (2001) argues that the impediment to organizing mass actions stems from the difficulty in coordination rather than from individuals’ resistance to contribute to the pursuit of a public good such as democratic change. He argues and other scholars confirm (Thomas et al., 2014) that common knowledge—mutual recognition of the knowledge of each other’s knowledge—eases risky coordination. This implies that coordination problems in authoritarian regimes should be particularly difficult to solve given the lack of available information, particularly of the sort that people willingly broadcast for others to share.

How Public Preferences Cause the Dictator’s and Dissidents’ Dilemmas, and Create Difficulties for the Masses

Not only do authoritarian regimes often—though not always—engage in censorship, but so too do members of the public living under dictatorial rule. In repressive environments, people often hesitate to share publicly their true preference if they believe they hold a minority opinion or if they fear they may be punished for expressing opposition to the regime (Kuran, 1991, 1995; Ginkel & Smith, 1999). Since many people only feel comfortable publicly expressing what they perceive to be the majority opinion—even if they do not share this opinion—it reinforces other people’s perception that the position they expressed is, in fact, the dominant opinion in society, which in turn leads others to misstate their publicly expressed opinion (Noelle-Neumann, 1974). In this environment neither the public nor the regime can gauge accurately the degree of support that the regime enjoys.

According to the dominant logic on collective action in high-risk environments, if an individual opposes the regime, before she would join an antigovernment mass action, she likely would first assess the relative strength of the opposition and the regime, and estimate the breadth of the underlying opposition among her compatriots in order to gauge how others might react if protests were to turn into a revolutionary movement (Shadmehr & Bernhardt, 2011). For example, she may know other people who, like her, also oppose the regime; yet she knows none of them has admitted this publicly. Therefore, she might conclude that the discord between her circle’s underlying and publicly expressed opinions probably occurs among other groups in society. In assessing underlying public support for the opposition, she therefore might discount the degree of publicly expressed support for the regime. The problem returns, however, to the lack of reliable information available to her that could help her determine the discount rate she should apply to arrive at the truth. Her tendency should still be to avoid participating because she likely would pay a higher cost if she were to mistakenly overestimate the discount rate—and thus underestimate the regime’s true support—and join a mass action that lacked support as opposed to underestimating the discount rate and remaining safely at home but discontent.

For a variety of practical and psychological reasons, people’s willingness to participate in costly actions often depends on the number of other people they anticipate will also participate. As James DeNardo’s (1985) book title suggests, there is “power in numbers.” As first actors protest, this information cascades to other citizens whose own participation was contingent on some threshold of prior participation (Granovetter, 1978; Kuran, 1991; Lohmann, 1994). Each person’s threshold can depend on a variety of factors including the degree of opposition she has for the regime, her tolerance of risk, and the degree she suffers psychologically from preference falsification. Participation in protest campaigns reaches equilibrium when the remaining latent participants’ thresholds remain higher than the actual level of participation. According to these arguments the unpredictability of the outcomes of protest cascades—whether they produce revolutions or peter out—does not stem from the uncertainty of the government repression, per se, but rather from the unknowable nature of the distribution of people’s true preferences throughout society (Kuran, 1991).

In competitive authoritarian regimes, however, information and coordination problems pose less of an obstacle to collective action, changing individual’s calculus to participate. Elections offer citizens an institutionalized route to mass mobilization, at times facilitated by the existence of political parties.

Why Vote in Authoritarian Elections? When Do Post-Electoral Protests Evolve into Nonviolent Revolution?

In earlier sections, I have discussed why dictators and opposition leaders would support and participate in elections in authoritarian regimes. However, for the elections to serve their purpose for each of these groups, enough citizens must turn out to vote at the polls. If, however, elections are noncompetitive or the electorate anticipates massive fraud, why do people turn out to vote short of being threatened by brute force? Few studies of competitive authoritarian regimes directly address the motivations of individual voters.

The studies that discuss individual motivations for voting behavior propose that two primary motivations drive voter turnout: voters expect some form of payment for doing so (Blaydes, 2011), or because voters see elections as a venue to express their dissatisfaction with the status quo (Miller, 2015). Evidence from Mubarak’s Egypt supports the former case, showing that the government manipulated budgets during election periods to appease different constituents, and even the average caloric intake of citizens increased during the run-up to the elections (Blaydes, 2011). In the latter case, although voters may not get to vote out the leader, with their vote they signal their dissatisfaction with the regime effectively demanding policy concessions in exchange for forgoing material benefits associated with voting. Regimes that experience negative electoral shocks to the vote count subsequently spend more on education and social welfare after the election (Miller, 2015).

Some people who have experienced years of authoritarian rule may have minimal faith that an election itself could bring about major policy change or a change in leadership. However elections can facilitate mobilization at a time when international observers have an eye on the country. Hence, some citizens may go to vote hoping the government does as expected and manipulates the results. The anticipation of fraudulent elections provides a rallying cry for the opposition and effectively lowers the cost for individuals of participating in mass protests (Tucker, 2007). Doug McAdam and Sidney Tarrow note that “disputed elections have become one of the most common catalysts of protest movements in non-democratic states” (2010, p. 534). Several authors concur, noting a coincidence between post-election protests and allegations of fraudulent outcomes (Calingaert, 2006; Kuzio, 2006; Tucker, 2007; Bunce & Wolchik, 2010). When fraud reaches such extreme levels that it leads election monitors to call into question the declared winner, the cost-benefit ratio of participation becomes even more favorable for individuals (Tucker, 2007).

In recent years as the lines have blurred between institutional characteristics of democratic and non-democratic regimes, so too have the distinctions between online and offline opposition activity. When protests appear to erupt, it may be difficult to decipher whether they were organized by a traditional social movement or if they evolved from communication among participant’s online social network.

Public Opinion and Protest in the Internet Age

Images of protests in Tahrir Square in January 2011 that eventually brought down the 30-year reign of Egypt’s then-dictator, Hosni Mubarak, remain indelibly etched in our minds. News coverage in the West highlighted the role that social media played in overcoming coordination problems. While many referred to the Egyptian revolution, and those of neighboring countries, as Twitter or Facebook revolutions (Zuckerman, 2011; Hudson, 2011),18 they were hardly the first such events in which citizens subjected to authoritarian rule turned to “new” ICTs to draw others to the streets. Scholars have argued that similar use of cellphones—first for texting and more recently to access social networking and video-sharing websites—helped citizens mobilize to force regime change in the Philippines in 2001 (Santner, 2010; Shirky, 2011) and Ukraine in 2004 (Goldstein, 2007), and publicly challenge results of elections in Iran (Kavanaugh et al., 2013) and Moldova (Morozov, 2009b) both in 2009, just to name a few instances.

Those who support the potential of ICTs contend that ICT access can facilitate antigovernment actions in authoritarian regimes through an informative mechanism, and via a tactical mechanism (Breuer, 2012; Diamond, 2012; Little, 2015). First, they increase access to information and a diverse array of perspectives in closed societies. Exposure to new, independent content opens the eyes of citizens, influencing their opinion of the regime and its performance—altering the cost-benefit ratio of action—potentially leading to a growing pool of prospective participants in antigovernment actions. Second, ICTs—text messaging, microblogging, and content-sharing, in particular—ease coordination problems inherent in mobilizing mass protest events. They facilitate the transmission of coordinating information among a network of opposition supporters and latent participants connected to these supporters.

Some attempts to demonstrate that new ICTs promote offline mobilization rely on country-level data to test broad implications of the relationship (e.g., higher Internet penetration rates or cellular subscription rates correlate with higher frequencies of demonstrations and riots) (e.g., Meier, 2011). To date, relatively few data exist at the organizational level (in part because many recent rebellions seem to lack “traditional” organizations behind them) or on individual participants, particularly in countries where mobilizing carries high costs. Given the lack of hard empirical data at the individual or group level, several scholars interested in the subject employ formal models. Alternatively, studies published in the wake of major international events relied on single case studies or comparing two to three, perhaps atypical, cases.

A few studies stand out for their effort to look at individual-level data through surveys and interviews with participants and, importantly, nonparticipants. Evidence drawn from surveys of people who participated in protests in Egypt in Tahrir Square in 2011 supports the importance of social media in shaping citizens’ decision to participate (Tufekci & Wilson, 2012). Other studies also have relied on content analyses of microblogs to show upticks in online communication prior to major protest actions (Howard & Hussain, 2011).

Skeptics of the power of ICTs point out that dissent long preceded the rise of the Internet, and that other nonviolent revolutions, such as those in Eastern Europe in 1989, occurred amid dictatorships prior to the Internet revolution. Students of Middle Eastern and North African countries contend that for the underlying dissent to take shape in the form of mass rebellions like those of the Arab Spring it required a mechanism to unite individual sentiments: “Digital media helped to turn individualized, localized, and community-specific dissent into a structured movement with a collective consciousness about both shared plights and opportunities for action” (Howard & Hussain, 2011, p. 41).

Not only does the information these mediums provide alter the dynamics of information control and information gathering in authoritarian regimes, but these technologies also change the methods through which people can access them, lowering the cost of reaching larger numbers of citizens. Increasingly, people access the Internet via mobile phones which overcomes the lack of personal computer ownership in developing countries. Mobile access to interactive communication technologies can aid in the rapid transmission of last-minute changes about logistics to avoid government forces. These factors may make ICTs, particularly cell phones, more influential for residents of dictatorships who cannot organize freely than for social movements in democracies.

To test whether the influence of ICT access on protest differs by regime type, I employ data on a smaller subset of countries that have better available information on protests. Many large-N studies on protests, which frequently rely on content analyses of newspapers to generate counts, ultimately produce relatively poor quality data. The Social Conflict Analysis Database (Salehyan et al., 2012) hosted by the Robert S. Strauss Center for International Security and Law at the University of Texas, Austin, released higher quality data on countries in Africa and parts of Latin America from 1990 to 2014. Using these data I compare the correlation between Internet penetration rates and the incidence of organized and spontaneous protests (i.e., demonstrations and riots) in democracies versus dictatorships (still relying on regime data from Magaloni et al., 2013 data). These data provide preliminary evidence that higher rates of Internet diffusion in authoritarian societies are associated with an increasing average numbers of protests in a given year, whereas little difference occurs in the average number of protests in democracies as countries’ Internet penetration rates increase. This distinction results in part because among the countries included more protests occur in dictatorships, but even taking that into consideration, the difference between regime types holds. The data also indicate that Internet access matters far more for spontaneous protests (where leaders are not clearly identifiable) than they do for organized ones, findings which suggest interesting implications for future research.19

Table 4 Average Number of Protests per Country-Year by Regime Type and Internet Penetration Rates, for Countries in the Social Conflict Analysis Databases of Africa and Latin America (1995–2013)

Democracies

Autocracies

Internet Penetration

Observations

Organized Protest

Spontaneous Protest

Total Protest

Observations

Organized Protest

Spontaneous Protest

Total Protest

Group 1 (<0.5%)

90

0.6

1.8

2.4

284

0.9

2.2

3.1

(1.1)a

(2.3)

(2.6)

(1.9)

(3.6)

(4.8)

Group 2 (≥0.5% and < 10.5%)

187

0.8

2.2

3.0

307

1.1

2.6

3.7

(1.7)

(3.5)

(4.4)

(2.5)

(5.8)

(7.1)

Group 3 (≥10.5% and < 25.5%)

59

0.6

2.8

3.5

65

2.6

5.4

8.0

(1.5)

(5.0)

(6.2)

(4.1)

(7.6)

(9.9)

Group 4 (≥25.5% and < 60.5%)

47

0.4

2.7

3.1

19

10.7

31.4

42.1

(1.0)

(3.8)

(4.3)

(26.9)

(64.1)

(86.1)

Group 5 (≥60.5%)

11

0.3

1.0

1.3

37

1.1

2.8

3.8

(0.5)

(1.7)

(1.9)

(3.0)

(7.2)

(10.0)

Note. These data rely on the Social Conflict Analysis Databases (SCAD) on Africa and Latin America and only include countries in their databases (Salehyan & Hendrix, 2014). Organized protest equals organized riots plus organized demonstrations. Spontaneous protest equals spontaneous riots plus spontaneous protests. Total protest sums the totals of organized and spontaneous protest. According to Salehyan and Hendrix, spontaneous protests were events in which they could not identify a leader, whereas organized protests were led by an identifiable person or organization.

a Observations are country-years. Standard errors appear in parentheses below mean number of events.

Two-sample t-tests with unequal variances of the means of total protest indicate with a 95% degree of confidence or higher that protest in autocracies exceeds that in democracies for groups 1, 3, and 4.

Early empirical studies on the relationship between ICT use and mobilization improve on impressions people reported in the immediate aftermath of particular events. Studies suggest that ICTs offer some promise for certain forms of mobilization in authoritarian regimes. However, to date, many authoritarian regimes have managed to catch up to the basic tactics, using measures like slowing down Internet speeds to inhibit uploading of content to video-sharing sites, or jamming cellular signals. Since these tactics affect not only active supporters of the opposition, but all residents in the area, a regime hoping to sustain whatever popularity it maintains and hold on to power must use these tactics sparingly.

Conclusion

This is a broad overview of the role of information in various forms for key actors in dictatorships, including members of the regime, dissident leaders, and the general public. The existing literature implies that information is crucial to the dynamic interactions among these actors, particularly in the contentious arenas of elections and collective actions. Not surprisingly, dictatorships create unique challenges for the control, dissemination, and acquisition of information.

Strategic secrecy on the part of the dictator leads other actors to question the truthfulness of information he disseminates. To gain credibility in these environments, leaders need to constrain their actions. To appease elites, they can adopt constraining institutions like semi-independent legislatures and elections. When they hope to mobilize the opposition to legitimize these institutions and the masses to demonstrate the strength of their support, dictators must make costly payments, or policy and procedural concessions to get the defiant participants to acquiesce.

Dissident leaders and the masses also find communication a difficult task. Dissident leaders often must take costly actions to earn the trust of the masses and help frame the benefits from collective actions in persuasive ways. When taking these actions, dissident leaders operate with limited quality information and must interpret signals from the government and other actors, which can dissuade people from acting or may lead to costly mistakes as the real meaning can get lost in the transmission of secretive information from dissident leaders to prospective participants.

Lastly, the masses need information to make everyday decisions, and more costly ones from time-to-time. For the public, information is a scarce resource in dictatorships. The true value of the product often remains unknown, making it a difficult decision for individuals to decide whether or not to invest their own limited resources to obtain it. They often depend on the behavior of others before deciding what actions to take.

While new and interesting studies emerge, the body of literature on information scarcity and civil unrest in dictatorships has room for improvement. There are a few key areas in which scholars could make inroads.

1.

Studies should be more explicit about the content of information that actors require, the nature of the information they do receive, and the transactions that occur to acquire information.

2.

The research that scholars produce could better serve larger audiences by presenting the material in more accessible ways, particularly those that employ formal models.

3.

Empirical studies likely need to move in the direction of looking at individual behavior. Cross-national research can only shed so much light on these relationships because most important changes occur at the individual level.

4.

Lastly, scholars need to look at China from a comparative perspective. It seems to be the most-studied authoritarian case, with fascinating insights about information, collective action, and authoritarian regimes, yet its comparability to other countries is questionable.

As world events have illustrated, and academic studies try to confirm, the nature of information and the methods for communicating it continually evolve. Innovations in technology lead to innovations in behavior, making this a dynamic, yet difficult, subject to research. Researchers also have grown (and have to grow) increasingly innovative in the ways they study some phenomena. As fast as technology changes, research methods also need to adapt. Network analysis, field experiments, and new forms of content analysis are just a few of the approaches scholars are using to contribute to the development of research on informational interactions and civil unrest in dictatorships.

References

  • Beaulieu, E., & Hyde, S. D. (2009). In the shadow of democracy promotion: Strategic manipulation, international observers and election boycotts. Comparative Political Studies, 42(3), 392–415.
  • Benford, R. D., & Snow, D. A. (2000). Framing processes and social movements: An overview and assessment. Annual Review of Sociology, 26, 611–639.
  • Bimber, B., Flanagin, A. J., & Stohl, C. (2005). Reconceptualizing collective action in the contemporary media environment. Communication Theory, 15(4), 365–388.
  • Blaydes, L. A. (2011). Elections and distributive politics in Mubarak’s Egypt. New York: Cambridge University Press.
  • Bob, C. (2005). The marketing of rebellion: Insurgents, media, and international activism. New York: Cambridge University Press.
  • Boix, C., & Svolik, M. W. (2013). The foundations of limited authoritarian government institutions: Commitment and power-sharing in dictatorships. Journal of Politics, 75(2), 300–316.
  • Brady, A. (2012). Market-friendly, scientific, high tech, politics-lite: China’s new approach to propaganda. In A. Brady (Ed.), China’s thought management (pp. 1–10). New York: Routledge.
  • Bratton, M., & van de Walle, N. (1997). Democratic experiments in Africa. New York: Cambridge University Press.
  • Breuer, A. (2012). The role of social media in mobilizing political protest: evidence from the Tunisian revolution. German Development Institute Discussion Paper 10/2012. Available at http://dx.doi.org/10.2139/ssrn.2179030.
  • Brockett, C. D. (1993). A protest cycle resolution of the repression/popular protest paradox. Social Science History, 17(3), 457–484.
  • Brockett, C. D. (2005). Political movements and violence in Central America. New York: Cambridge University Press.
  • Bueno de Mesquita, E. (2010). Regime change and revolutionary entrepreneurs. American Political Science Review, 104(3), 446–466.
  • Bunce, V. J., & Wolchik, S. L. (2010). Defeating dictators: Electoral change and stability in competitive authoritarian regimes. World Politics, 62(1), 42–86.
  • Calingaert, D. (2006). Election rigging and how to fight it. Journal of Democracy, 17(3), 138–151.
  • Chwe, M. S. (2001). Rational ritual: Culture, coordination and common knowledge. Princeton, NJ: Princeton University Press.
  • Collings, A. (2001). Words of fire: Independent journalists who challenge dictators, drug lords, and other enemies of a free press. New York: New York University Press.
  • Darling, J. (2008). Latin America, media, and revolution. New York: Palgrave MacMillan.
  • DeNardo, J. (1985). Power in numbers: The political strategy of protest and rebellion. Princeton, NJ: Princeton University Press.
  • Dewan, T., & Myatt, D. P. (2008). The qualities of leadership: Direction, communication, and obfuscation. American Political Science Review, 102(3), 351–368.
  • Diamond, L. (2010). Liberation technology. Journal of Democracy, 21(3), 69–83.
  • Diamond, L. (2012). “Introduction” and “Liberation technology.” In L. Diamond & M. F. Plattner (Eds.), Liberation Technology: Social Media and the Struggle for Democracy (pp. ix–xxvi & 3–17). Baltimore: The John Hopkins University Press.
  • Earl, J. (2003). Tanks, tear gas, and taxes: Toward a theory of movement repression. Sociological Theory, 21(1), 44–68.
  • Edmond, C. (2013). Information manipulation, coordination, and regime change. Review of Economic Studies, 80(4), 1422–1458.
  • Egorov, G., Guriev, S. M., & Sonin, K. (2009). Why resource-poor dictators allow freer media: A theory and evidence from panel data. American Political Science Review, 103(4), 645–668.
  • Esarey, A., & Qiang, X. (2011). Digital communication and political change in China. International Journal of Communication, 5, 289–319.
  • Francisco, R. A. (1993). Theories of protest and the revolutions of 1989. American Journal of Political Science, 37(3), 663–680.
  • Frantz, E., & Kendall-Taylor, A. (2014). A dictator’s toolkit: Understanding how co-optation affects repression in autocracies. Journal of Peace Research, 51(3), 332–346.
  • Frantz, E., & Stein, E. A. (2012). Comparative leadership in non-democracies. In L. Helms (Ed.), Comparative political leadership (pp. 292–313). Basingstoke, U.K.: Palgrave Macmillan.
  • Frantz, E., & Stein, E. A. (2016) Countering Coups: Leadership Succession Rules in Dictatorships. Comparative Political Studies, 1–29.
  • Freedom House. (2013). Detailed data and subscores 1980–2012. In Freedom House, 2013 Freedom in the World Data. Washington, DC: Freedom House.
  • Gandhi, J., & Przeworski, A. (2006). Cooperation, cooptation, and rebellion under dictatorships. Economics & Politics, 18(1), 1–26.
  • García-Avilés, J. A., Kaltenbrunner, A., & Meier, K. (2014). Media convergence revisited. Journalism Practice, 8(5), 573–584.
  • Garrido, M., & Halavais, A. (2003). Mapping networks of support for the Zapatista movement: Applying social-networks analysis to study contemporary social movements. In M. McCaughy & M. D. Ayers (Eds.), Cyberactivism: Online activism in theory and practice (pp. 165–184). London: Routledge.
  • Geddes, B. (2006). Why parties and elections in authoritarian regimes. Revised version of paper presented at the 2005 American Political Science Association Annual Meeting. Washington DC, September 1, 2005.
  • Geddes, B., & Zaller, J. (1989). Sources of popular support for authoritarian regimes. American Journal of Political Science, 33(2), 319–347.
  • Gehlbach, S., & Keefer, P. (2011). Investment without democracy: Ruling party institutionalization and credible commitment in autocracies. Journal of Comparative Economics, 39, 123–139.
  • Ginkel, J., & Smith, A. (1999). So You Say You Want a Revolution: A Game Theoretic Explanation of Revolution in Repressive Regimes. The Journal of Conflict Resolution, 43(3), 291–316.
  • Gladwell, M. (2010). Small change: Why the revolution will not be tweeted. The New Yorker. http://www.newyorker.com/reporting/2010/10/04/101004fa_fact_gladwell?currentPage=all.
  • Goldstein, J. (2007). The role of digital networked technologies in the Ukrainian Orange Revolution. Berkman Center Research Publication No. 2007–14, Berman Center for Internet and Society at Harvard University.
  • Goodwin, J. (2011). Why we were surprised (again) by the Arab Spring. Swiss Political Science Review, 17(4), 452–456.
  • Granovetter, M. (1978). Threshold models of collective behavior. American Journal of Sociology, 83(6), 1420–1443.
  • Guriev, S., & Treisman, D. (2015). How modern dictators survive: cooptation, censorship, propaganda, and repression. Centre for Economic and Policy Research (CEPOR) Working Paper DP10454. Available at http://www.cepr.org/active/publications/discussion_papers/dp.php?dpno=10454.
  • Haugbølle, R. H., & Cavatorta, F. (2011). Will the real Tunisian opposition please stand up? Opposition coordination failures under authoritarian constraints. British Journal of Middle Eastern Studies, 38(3), 323–341.
  • Howard, M. M., & Roessler, P. G. (2006). Liberalizing electoral outcomes in competitive authoritarian regimes. American Journal of Political Science, 50(2), 365–381.
  • Howard, P. N., & Hussain, M. M. (2011). The role of digital media. Journal of Democracy, 22(3), 35–48.
  • Hudson, J. (2011, January 31). The ‘Twitter Revolution’ debate: The Egyptian test case.” Atlantic Wire.
  • Hussain, M. M., & Howard, P. N. (2013). What best explains successful protest cascades? ICTs and the fuzzy causes of the Arab Spring. International Studies Review, 15(1), 48–66.
  • Hyde, S. D. (2011). Catch us if you can: Election monitoring and international nor creation. American Journal of Political Science, 55, 201–462.
  • Kalathil, S. (2003). Dot.com for Dictators. Foreign Policy, 135(March–April), 42–49.
  • Kalathil, S., & Boas, T. C. (2003). Open networks, closed regimes. New York: Carnegie International Endowment for Peace.
  • Kavanaugh, A., Sheetz, S. D., Hassan, R., Yang, S., Elmongui, H. G., Fox, E. A., Magdy, M., & Shomemaker, D. J. (2013). Between a rock and a cell phone: Communication and information technology use during the 2011 uprisings in Tunisia and Egypt. International Journal of Information Systems for Crisis Response and Management, 5(1), 1–21.
  • Kellam, M., & Stein, E. A. (2015). Silencing critics: Why and how presidents restrict media freedom in democracies. Comparative Political Studies.
  • Keller, J. (2010, June 18). Evaluating Iran’s Twitter Revolution. The Atlantic.
  • Kelley, J. (2011). Do international election monitors increase or decrease opposition boycotts? Comparative Political Studies, 44(11), 1527–1556.
  • Kendall-Taylor, A., & Frantz, E. 2014. Mimicking democracy to prolong autocracies. The Washington Quarterly, 37(4), 71–84.
  • Kenez, P. (1985). The birth of the propaganda state: Soviet methods of mass mobilization, 1917–1929. New York: Cambridge University Press.
  • Khawaja, M. (1993). Repression and popular collective action: Evidence from the West Bank. Sociological Forum, 8(1), 47–71.
  • King, G., Pan, J., & Roberts, M. E. (2013). How censorship in China allows government criticism but silences collective expression. American Political Science Review, 107(2), 326–343.
  • Kuran, T. (1991). Now out of never: The element of surprise in Eastern European Revolution of 1989. World Politics, 44(1), 7–48.
  • Kuran, T. (1995). Private truths, public lies. Cambridge, MA: Harvard University Press.
  • Kurzman, C. (1996). Structural opportunity and perceived opportunity in social-movement theory: The Iranian Revolution of 1979. American Sociological Review, 61(1), 153–170.
  • Kushnir, B. (2004). Cães de guarda: Jornalistas e censores, do AI-5 à Constituição de 1988. São Paulo: Boitempo Editoral.
  • Kuzio, T. (2006). Civil society, youth and societal mobilization in democratic revolutions. Communist and Post-Communist Studies, 39(3), 365–386.
  • Levitsky, S., & Way, L. (2002). The rise of competitive authoritarianism. Journal of Democracy, 13(2), 51–65.
  • Lichbach, M. I. (1994a). Rethinking rationality and rebellion: Theories of collective action and problems of collective dissent. Rationality and Society, 6(1), 8–39.
  • Lichbach, M. I. (1994b). What makes rational peasants revolutionary? Dilemma paradox, and irony in collective action. World Politics, 45(3), 383–418.
  • Lichbach, Mark I. (1987). Deterrence or escalation? The puzzle of aggregate studies of repression and dissent. Journal of Conflict Resolution, 31(2), 266–297.
  • Lindberg, S. I. (2006). Opposition parties and democratisation in Sub-Saharan Africa. Journal of Contemporary African Studies, 24(1), 123–138
  • Linz, J. J. (2000). Totalitarian and authoritarian regimes. Boulder, CO: Lynne Rienner.
  • Little, A. T. (2012). Elections, fraud, and election monitoring in the shadow of revolution. Quarterly Journal of Political Science, 7, 249–283.
  • Little, A. T. (2015). Communication technology and protest. Journal of Politics, 78(1). http://www.jstor.org/stable/10.1086/683187?origin=JSTOR-pdf.
  • Lohmann, S. (1993). A Signaling Model of Informative and Manipulative Political Action. The American Political Science Review, 87(2), 319–333.
  • Lohmann, S. (1994). The dynamics of informational cascades: The Monday Demonstrations in Leipzig, East Germany, 1989‒91. World Politics, 47(1), 42–101.
  • Lohmann, S. (2000). Collective action cascades: An informational rationale for the power in numbers. Journal of Economic Surveys, 14(5), 655–684.
  • Lorentzen, P. (2013). Regularizing rioting: Permitting public protest in an authoritarian regime. Quarterly Journal of Political Science, 8, 127–158.
  • Lorentzen, P. (2014). China’s strategic censorship. American Journal of Political Science, 58(2), 402–414.
  • MacKinnon, R. (2011). China’s “networked authoritarianism.” Journal of Democracy, 22(2), 32–46.
  • Magaloni, B. (2008). Credible power sharing and the longevity of authoritarian rule. Comparative Political Studies, 41(4–5), 715–774.
  • Magaloni, B. (2010). The game of electoral fraud and the ousting of authoritarian rule. American Journal of Political Science, 54(3), 751–765.
  • Magaloni, B., Chu, J., & Min, E. (2013). Autocracies of the world, 1950–2012 (Version 1.0). Dataset, Stanford University.
  • Malesky, E., & Schuler, P. (2010). Nodding or needing: Analyzing delegate responsiveness in an authoritarian parliament. American Political Science Review, 104(3), 382–502.
  • Malesky, E., & Schuler, P. (2011). The Single-Party Dictator’s Dilemma: Information in Elections without Opposition. Legislative Studies Quarterly, 36(4), 491–530.
  • Marconi, P. (1980). A censura política na imprensa Brasileira, 1968–1978. São Paulo: Global Editora.
  • Mason, T. D., & Krane, D. A. (1989). The political economy of death squads: Toward a theory of the impact of state-sanctioned terror. International Studies Quarterly, 33(2), 175–198.
  • Masters, D. (2004). Support and nonsupport for nationalist rebellion: A prospect theory approach. Political Psychology, 25(5), 703–726.
  • McAdam, D., & Tarrow, S. (2010). Ballots and barricades: On the reciprocal relationship between elections and social movements. Perspectives on Politics, 8(2), 529–542.
  • Meier, P. P. (2011). Do “liberation technologies” change the balance of power between repressive states and civil society (PhD diss., Fletcher School of Law and Diplomacy, Medford, MA). http://irevolution.files.wordpress.com/2011/11/meier-dissertation-final.pdf.
  • Miller, M. K. (2015). Elections, information, and policy responsiveness in autocratic regimes. Comparative Political Studies, 48(12), 1526–1562.
  • Milner, H. (2006). The digital divide: The role of political institutions in technology diffusion. Comparative Political Studies, 39(2), 176–199.
  • Morgan, P., Brock, J., & Foden, G. (2006). The Last King of Scotland. Film. Directed by Kevin Macdonald. Los Angeles: 20th Century Fox.
  • Morozov, E. (2009a). Moldova’s Twitter revolution is NOT a myth. Foreign Policy.
  • Morozov, E. (2009b). Iran: Downside to the “Twitter Revolution.” Dissent, 56(4), 10–14.
  • Muller, E. N., & Weede, E. (1990). Cross-national variation in political violence: A rational-action approach. Journal of Conflict Resolution, 34(4), 624–651.
  • Noelle-Neumann, E. (1974). The spiral of silence: A theory of public opinion. Journal of Communication, 24(2), 43–51.
  • O’Donnell, G. (1978). Reflections on the patterns of change in the bureaucratic-authoritarian state. Latin American Research Review, 13(1), 3–38.
  • Opp, K., & Roehl, W. (1990). Repression, micromobilization and political protest. Social Forces, 69(2), 521–547.
  • O’Shaughnessy, N. (2009). Selling Hitler: Propaganda and the Nazi brand. Journal of Public Affairs, 9(1), 55–76.
  • Polese, A., & Ó’Beacháin, D. (2011). The Color Revolution virus and authoritarian antidotes: Political protest and regime counterattacks in post-communist spaces. Demokratizatsiya, 9(2), 111–132.
  • Rasler, K. (1996). Concessions, repression, and political protest in the Iranian Revolution. American Sociological Review, 61(1), 132–152.
  • Remmer, K., & Merkx, G. W. (1982). Bureaucratic-authoritarianism revisited. Latin American Research Review, 17(2), 3–40.
  • Ritter, D. P., & Trechsel, A. H. (2014). Revolutionary cells: On the role of texts, tweets, and status updates in unarmed revolutions. In B. Grofman, A. H. Trechsel, & M. Franklin (Eds.), The Internet and democracy in global perspective: Voters, candidates, parties and social movements (pp. 111–128). Cham, Switzerland: Springer International Publishing Switzerland.
  • Ritter, E. H., & Conrad, C. H. (2016). Preventing and responding to dissent: The observational challenges of explaining strategic repression. American Political Science Review, 110(1), 85–99.
  • Rød, E. G., & Weidmann, N. B. (2015). Empowering activists or autocrats? The Internet in authoritarian regimes. Journal of Peace Research, 52(3), 338–351.
  • Rosenberg, T. (1987). Letter from Chile. Columbia Journalism Review, 26(3), 49–51.
  • Salehyan, I., & Hendrix, C. (2014). Social conflict in analysis database (Version 3.1). http://www.scaddata.org.
  • Salehyan, I., Hendrix, C. S., Hamner, J., Case, C., Linebarger, C., Stull, E., & Williams, J. (2012). Social conflict in Africa: A new database. International Interactions, 38(4), 503–511.
  • Santner, V. (2010). The SMS Revolution: The impact of mobile phones on political protest using the example of the EDSA II movement in the Philippines in 2001(Master’s thesis, Universität Wien). http://othes.univie.ac.at/9059/1/2010-03-28_0304108.pdf.
  • Schedler, A. (2002). The nested game of democratization by elections. International Political Science Review, 23(1), 103–122.
  • Schedler, A. (2006). Electoral authoritarianism: The dynamics of unfree competition. Boulder, CO: Lynne Rienner.
  • Schulz, M. S. (1998). Collective action across borders: Opportunity structures, network capacities, and communicative praxis in the age of advanced globalization. Sociological Perspectives, 41(3), 587–616.
  • Shadmehr, M., & Bernhardt, D. (2011). Collective action with uncertain payoffs: Coordination, public signals and punishment dilemmas. American Political Science Review, 105(4), 819–851.
  • Shirky, C. (2011). The political power of social media: Technology, the public sphere, and political change. Foreign Affairs, 90(1), 28–41.
  • Siegel, D. A. (2011). When does repression work? Collective action in social networks. Journal of Politics, 73(4), 993–1010.
  • Snider, E. A., & Faris, D. M. (2011). The Arab Spring: U.S. democracy promotion in Egypt. Middle East Policy, 18(3), 49–62.
  • Stein, E. A. (2013). The unraveling of support for authoritarianism: The dynamic relationship of media, elites and public opinion in Brazil, 1972‒1982. International Journal of Press/Politics, 8(1), 85–107.
  • Stein, E.A. (2016). Censoring the Press: A Barometer of Government Tolerance for Anti-regime Dissent under Authoritarian Rule. Journal of Politics in Latin America, 8(2), 101–142.
  • Stockmann, D., & Gallagher, M. E. (2011). Remote control: How media sustain authoritarian rule in China. Comparative Political Studies, 44(4), 436–467.
  • Thomas, K. A., DeScioli, P., Haque, O. S., & Pinker, S. (2014). The psychology of coordination and common knowledge. Journal of Personality and Social Psychology, 107(4), 657–676.
  • Tucker, J. A. (2007). Enough! electoral fraud, collective action problems, and post-communist colored revolutions. Perspectives on Politics, 5(3), 535–551.
  • Tufekci, Z., & Wilson, C. (2012). Social media and the decision to participate in political protest: Observations from Tahrir Square. Journal of Communication, 62(2), 363–379.
  • VonDoepp, P., & Young, D. J. (2015). Holding the state at bay: Understanding media freedoms in Africa. Democratization.
  • Vu, K. (2011). ICT as a source of economic growth in the information age: Empirical evidence from the 1996‒2005 period. Telecommunications Policy, 35, 357–372.
  • Weinstein, J. (2006). Inside rebellion: The politics of insurgent violence. New York: Cambridge University Press.
  • Whitten-Woodring, J. (2009). Watchdog or lapdog? Media freedom, regime type, and government respect for human rights. International Studies Quarterly, 53(3), 595–625.
  • Whitten-Woodring, J., & James, P. (2012). Fourth estate or mouthpiece? A formal model of media, protest, and government repression. Political Communication, 29(2), 113–136.
  • Wintrobe, R. (1998). The political economy of dictatorship. New York: Cambridge University Press.
  • World Bank. (2014). World development indicators. Washington, DC: World Bank. http://Data.worldbank.org/data-catalog/world-development-indicators.
  • Wright, J. (2008a). Do authoritarian institutions constrain? How legislatures affect economic growth and investment. American Journal of Political Science, 52(2), 322–343.
  • Wright, J. (2008b). To invest or insure? How authoritarian time horizons impact. Comparative Political Studies, 41(7), 971–1000.
  • Zaller, J. (2003). A new standard of news quality: Burglar alarms for the monitorial citizen. Political Communication, 20(2), 109–130.
  • Zuckerman, E. (2011, January 14). The first Twitter Revolution? Foreign Policy. http://www.foreignpolicy.com/articles/2011/01/14/the_first_twitter_revolution.

Notes

  • 1. Throughout this article, I use authoritarian regime, autocratic regime, and dictatorship interchangeably. Likewise, I refer to the leader as the dictator, autocrat, or authoritarian leader with no difference in meaning intended.

  • 2. Unfortunately, the manner in which some authors present their models substantially limits the audience who can consume them, making it unlikely that professors would incorporate the material into undergraduate or even some graduate courses.

  • 3. For a more extensive discussion of this perspective of media freedom, see the analysis of what comprises media freedom in Kellam and Stein (2015, pp. 7–8).

  • 4. Detailed data and methodological descriptions available through the Freedom House website. 2013 Freedom in the World Data. Washington, DC: Freedom House. http://www.freedomhouse.org/report-types/freedom-press.

  • 5. For the purposes of these tables, I created a variable “income groups,” based on a country’s annual GDP per capita ppp (2011 constant international dollars), that groups countries by year into seven categories according to average annual income: 0–$1,000, $1,001–$5,000, $5,001–$10,000, $10,001–$20,000, $20,001–$30,000, $30,001–$40,000, and over $40,000. They rely on arbitrary cut-off points, not based on percentiles, and, thus, each group contains a different number of country-years.

  • 6. The variable name is demo_r and is binary. See Magaloni et al. (2013).

  • 7. For more on authoritarian regimes that incorporate democratic features, see Levitsky and Way (2002), and Schedler (2006).

  • 8. John Zaller (2003) uses this expression in reference to people’s critique of poor news quality associated with market-driven journalism, which he contends is good enough at getting the attention of citizens to alert the police in time to catch to the metaphorical burglar (or in this case corrupt or ineffective politicians).

  • 9. Vu (2011) notes that the expansion of ICT access has diminishing returns at high rates of penetration. At high levels of Internet penetration, additional expansion of Internet access has little effect on economic performance.

  • 10. The differences in the means of Internet penetration between autocracies and democracies are statistically significant, based on two-way t-tests, for all but one of the income groups (The exception being country-years with a GDP per capita ppp between $5,001 and $10,000.)

  • 11. I focus on unarmed, mass mobilization. For an excellent discussion of the information challenges insurgent leaders face, see Jeremy Weinstein’s (2006) book, Inside Rebellion: The Politics of Insurgent Violence.

  • 12. The literature on the subject is too expansive to review fully here. For some examples, see DeNardo (1985), Lichbach (1987, 1994a), Mason and Krane (1989), Opp and Roehl (1990), Brockett (1993), Khawaja (1993), Rasler (1996), and Siegel (2011).

  • 13. For a review on the use of framing in collective action and social movements, see Robert Benford and David Snow’s (2000) review on the subject.

  • 14. See, e.g., Dewan and Myatt (2008), Shadmehr and Bernhardt (2011), and Edmond (2013).

  • 15. Since I address a historical case, I refer to mainstream media, specifically traditional printed newspapers. Arguably the actions modern authoritarian regimes take against well-known bloggers after posting critical content or observing content disappear and finding blocked pages could serve a similar purpose for today’s dissident leaders, though I suspect they would be less efficient signals. Unlike content that appears above the fold on a newspaper (and is thus seen by passersby), the ephemeral nature of web content and the personalization of home pages means that we can never be sure that others see the same content we do.

  • 16. By changes in content, I do not refer to developments in the news over time, but rather trends in the type of news that the government permits. Studies have suggested that all authoritarian regimes consider certain topics taboo, such as coverage of corruption by top-level government officials or exposés on the leader’s family (Collings, 2001).

  • 17. Due to inconsistent data on participation numbers, I could not test implications about changes in the number of participants based on previous media coverage, just the initiation or not, of new mass actions.

  • 18. For that matter, Tunisia and Egypt were not even the first so-called Twitter Revolutions. Evgeny Morozov (2009a) and Jared Keller (2010) each used the term to refer to 2009 post-election civil unrest in Moldova and Iran, respectively. Unlike in Tunisia and Egypt, however, these would-be revolutions did not materialize.

  • 19. See the SCAD codebook for an elaboration on the difference between spontaneous and organized events, available at https://www.strausscenter.org/scad.html (Salehyan et al., 2012).