Tag Archives: Dictatorship

Introduction to Digital Origins of Dictatorship and Democracy

Reading Philip Howard’s “Digital Origins of Dictatorship and Democracy” and Evgeny Morozov’s “Net Delusion” back-to-back over a 10-day period in January was quite a trip. The two authors couldn’t possibly be more different in terms of tone, methodology and research design. Howard’s approach is rigorous and balanced. He takes a data-driven, mixed-methods approach that ought to serve as a model for the empirical study of digital activism.

In contrast, Morozov’s approach frequently takes the form of personal attacks, snarky remarks and cheap rhetorical arguments. This regrettably drowns out the important and valid points he does make in some chapters. But what discredits Net Delusion the most lies not in what Morozov writes but in what he hides. To say the book is one-sided would be an understatement. But this has been a common feature of the author’s writings on digital activism, and one of the reasons  I took him to task a couple years ago with my blog posts on anecdote heaven. If you follow that back and forth, you’ll note it ends with personal attacks by Morozov mixed with evasive counter-arguments. For an intelligent and informed critique of Net Delusion, see my colleague Mary Joyce’s blog posts.

In this blog post, I summarize Howard’s introductory chapter. For a summary of his excellent prologue, please see my previous post here.

The introductory chapter to Digital Origins provides a critique of the datasets and methodologies used to study digital activism. Howard notes that the majority of empirical studies, “rely on a few data sources, chiefly the International Telecommunications Union, the World Bank, and the World Resources Institute. Indeed, these organizations often just duplicate each other’s poor quality data. Many researchers rely heavily on this data for their comparative or single-country case studies, rather than collecting original observations or combining data in interesting ways. The same data tables appear over and over again.”

I faced this challenge in my dissertation research. Collecting original data is often a major undertaking. Howard’s book is the culmination of 3-4 years of research supported by important grants and numerous research assistants. Alas, PhD students don’t always get this kind of support. The good news is that Howard and others are sharing their new datasets like the Global Digital Activism Dataset.

In terms of methods, there are limits in the existing literature. As Howard writes,

“Large-scale, quantitative, and cross-sectionalstudies must often collapse fundamentally different political systems—autocracies, democracies, emerging democracies, and crisis states—into afew categories or narrow indices. […] Area studies that focus on one or two countries get at the rich history of technology diffusion and political development, but rarely offer conclusions that can be useful in understanding some of the seemingly intractable political and security crises in other parts of the world.”

Howard thus takes a different approach, particularly in his quantitative analysis, and introduces fuzzy set logic:

“Fuzzy set logic offers general knowledge through the strategy of looking for shared causal conditions across multiple instances of the same outcome—sometimes called ‘selecting on the dependent variable.’ For large-N, quantitative, and variable oriented researchers, this strategy is unacceptable because neither the outcome nor the shared causal conditions vary across the cases. However, the strategy of selecting on the dependent variableis useful when researchers are interested in studying necessary conditions, and very useful when constructing a new theoretically defined population such as ‘Islamic democracy.’

“Perhaps most important, this strategy is most useful when developing theory grounded in the observed, real-world experience of democratization in the Muslim communities ofthe developing world, rather than developing theory by privileging null, hypothetical, and unobserved cases.”

Using original data and this new innovative statistical approach, Howard finds that “technology diffusion has had a crucial causal role in improvements in democratic institutions.”

“I find that technology diffusion has become, in combination with otherfactors, both a necessary and suffi cient cause of democratic transition or entrenchment.”

“Protests and activist movements have led to successful democratic insurgencies, insurgencies that depended on ICTs for the timing and logistics of protest. Sometimes democratic transitions are the outcome, and sometimes the outcome is slight improvement in the behavior of authoritarianstates. Clearly the internet and cell phones have not on their owncaused a single democratic transition, but it is safe to conclude that today, no democratic transition is possible without information technologies.”

My next blog post on Howard’s book will summarize Chapter 1: Evolution and Revolution, Transition and Entrenchment.

Access to Mobile Phones Increases Protests Against Repressive Regimes

I recently shared a draft of my first dissertation chapter which consists of a comprehensive literature review on the impact of Information and Communication Technologies (ICTs) on Democracy, Activism and Dictatorship. Thanks very much to everyone who provided feedback, I really appreciate it. I will try to incorporate as much of the feedback as possible in the final version and will also update that chapter in the coming months given the developments in Tunisia and Egypt.

The second chapter of my dissertation comprises a large-N econometric study on the impact of ICT access on anti-government protests in countries under repressive rule between 1990 and 2007. A 32-page draft of this chapter is available here as a PDF. I use negative binomial regression analysis to test whether the diffusion of ICTs is a statistically significant predictor of protest events and if so, whether that relationship is positive or negative. The dependent variable, protests, is the number of protests per country-year. The ICT variables used in the model are: Internet users, mobile phone subscribers and number of telephone landlines per country-year. The control variables, identified in the literature review are percentage change in GDP, unemployment rate, the degree of autocracy per country-year, internal war and elections.

A total of 38 countries were included in the study: Algeria, Armenia, Azerbaijan, Bahrain, Belarus, Burkina Faso, Burma, China, Cote d’Ivoire, Cuba, DRC, Egypt, Gabon, Guinea, India, Iran, Iraq, Jordan, Kazakhstan, Kenya, Malaysia, Morocco, Pakistan, Philippines, Russia, Saudi Arabia, Singapore, Sudan, Syria, Tajikistan, Thailand, Tunisia, Turkey, Ukraine, United Arab Emirates, Uzbekistan, Venezuela and Zimbabwe. I clustered these countries into 4 groups, those with relatively (1) high and (2) low levels of ICT access; and those with (3) high and (4) low levels of protests per country-year. The purpose of stratifying the data is to capture underlying effects that may be lost by aggregating all the data. So I ran a total of 5 regressions, one on each of those four country groups and one on all the countries combined.

All five negative binomial regression models on the entire 18-year time panel for the study data were significant. Of note, however, is the non-significance of the Internet variable in all models analyzed. Mobile phones were only significant in the regression models for the “Low Protest” and “High Mobile Phone Use” clusters. However, the relationship was negative in the former case and positive in the latter. In other words, an increase in mobile phone users in countries with relatively high ICTs access, is associated with an increase in the number of protests against repressive regimes. This may imply that social unrest is facilitated by the use of mobile communication in countries with widespread access to mobile phones, keeping other factors constant.

These findings require some important qualifications. First, as discussed in the data section, the protest data may suffer from media bias. Second, the protest data does not provide any information on the actual magnitude of the protests. Third, economic data on countries under repressive rule need to be treated with suspicion since some of this data is self-reported. For example, authoritarian regimes are unlikely to report the true magnitude of unemployment in their country. ICT data is also self-reported. Fourth, the data is aggregated to the country-year level, which means potentially important sub-national and sub-annual variations are lost. Fifth and finally, the regression results may be capturing other dynamics that are not immediately apparent given the limits of quantitative analysis.

Qualitative comparative analysis is therefore needed to test and potentially validate the results derived from this quantitative study. Indeed, “perhaps the best reason to proceed in a qualitative and comparative way is that the categories of ‘democracy’ and ‘technology diffusion’ are themselves aggregates and proxies for other measurable phenomena” (Howard 2011). Unpacking and then tracing the underlying causal connections between ICT use and protests requires qualitative methodologies such process-tracing and semi-structured interviews. The conceptual framework developed in Chapter 2 serves as an ideal framework to inform both the process-tracing and interviews. The next chapter of my dissertation will thus introduce two qualitative case studies to critically assess the impact of ICTs on state-society relations in countries under repressive rule. In the meantime, I very much welcome feedback on this second chapter from iRevolution readers.

ICTs, Democracy, Activism and Dictatorship: Comprehensive Literature Review

Building on my previous post with respect to Howard Philip’s “Origin of Dictatorship and Democracy,” I’ve completed a draft of my dissertation chapter which comprises a comprehensive literature on the impact of Information and Communication Technologies (ICTs) on Democracy, Activism and Dictatorship. This is a 54-page document (17,000+ words)  which I believe represents the most up-to-date and in-depth review of the literature currently available. The chapter reviews both the quantitative and qualitative literature in this space.

You can download the chapter here (PDF).

I’m actively looking for feedback to make the chapter even stronger and more useful to scholars and practitioners interested in this space. So please do add any recommendations you may have in the comments section below. Thank you very much!