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" Eight years after the Arab Spring there is still much debate over the link between Internet technology and protest against authoritarian regimes. While the debate has advanced beyond the simple question of whether the Internet is a tool of liberation or one of surveillance and propaganda, theory and empirical data attesting to the circumstances under which technology benefits autocratic governments versus opposition activists is scarce. In this book, Nils B. Weidmann and Espen Geelmuyden Rød offer a broad theory about why and when digital technology is used for one end or another, drawing on detailed empirical analyses of the relationship between the use of Internet technology and protest in autocracies. By leveraging new sub-national data on political protest and Internet penetration, they present analyses at the level of cities in more than 60 autocratic countries. The book also introduces a new methodology for estimating Internet use, developed in collaboration with computer scientists and drawing on large-scale observations of Internet traffic at the local level. Through this data, the authors analyze political protest as a process that unfolds over time and space, where the effect of Internet technology varies at different stages of protest. They show that violent repression and government institutions affect whether Internet technology empowers autocrats or activists, and that the effect of Internet technology on protest varies across different national environments. "--

Researchers now have greater access to granular georeferenced (i.e., spatial) data on social and political phenomena than ever before. Such data have seen wide use, as they offer the potential for researchers to analyze local phenomena, test mechanisms, and better understand micro-level behavior. With these political event data, it has become increasingly common for researchers to select the smallest spatial scale permitted by the data. We argue that this practice requires greater scrutiny, as smaller spatial or temporal scales do not necessarily improve the quality of inferences. While highly disaggregated data reduce some threats to inference (e.g., aggregation bias), they increase the risk of others (e.g., outcome misclassification). Therefore, we argue that researchers should adopt a more principled approach when selecting the spatial scale for their analysis. To help inform this choice, we characterize the aggregation problem for spatial data, discuss the consequences of too much (or too little) aggregation, and provide some guidance for applied researchers. We demonstrate these issues using both simulated experiments and an analysis of spatial patterns of violence in Afghanistan.

AbstractMost measures of social conflict processes are derived from primary and secondary source reports. In many cases, reports are used to create event‐level data sets by aggregating information from multiple, and often conflicting, reports to single event observations. We argue that this pre‐aggregation is less innocuous than it seems, costing applied researchers opportunities for improved inference. First, researchers cannot evaluate the consequences of different methods of report aggregation. Second, aggregation discards report‐level information (i.e., variation across reports) that is useful in addressing measurement error inherent in event data. Therefore, we advocate that data should be supplied and analyzed at the report level. We demonstrate the consequences of using aggregated event data as a predictor or outcome variable, and how analysis can be improved using report‐level information directly. These gains are demonstrated with simulated‐data experiments and in the analysis of real‐world data, using the newly available Mass Mobilization in Autocracies Database (MMAD).

The reported role of social media in recent popular uprisings against Arab autocrats has fueled the notion of 'liberation technology', namely that information and communication technology (ICT) facilitates organization of antigovernment movements in autocracies. Less optimistic observers, on the other hand, contend that ICT is a tool of repression in the hands of autocrats, imposing further restrictions on political and social liberties. We investigate whether the liberation- or the repression-technology perspective can better explain empirically observed patterns. To this end, we analyze two outcomes. First, we look at which autocracies are more likely to adopt and expand the Internet. In line with the repression technology expectation, we find that regimes aiming to prevent any independent public sphere are more likely to introduce the Internet. Second, we study the effects of the Internet on changes towards democracy. This analysis reveals no effect of the Internet on political institutions. These findings provide moderate support for the 'repression technology' perspective, and suggest that the Internet has not – at least in its first two decades of existence – contributed to a global shift towards democracy.

The reported role of social media in recent popular uprisings against Arab autocrats has fueled the notion of 'liberation technology', namely that information and communication technology (ICT) facilitates organization of antigovernment movements in autocracies. Less optimistic observers, on the other hand, contend that ICT is a tool of repression in the hands of autocrats, imposing further restrictions on political and social liberties. We investigate whether the liberation- or the repression-technology perspective can better explain empirically observed patterns. To this end, we analyze two outcomes. First, we look at which autocracies are more likely to adopt and expand the Internet. In line with the repression technology expectation, we find that regimes aiming to prevent any independent public sphere are more likely to introduce the Internet. Second, we study the effects of the Internet on changes towards democracy. This analysis reveals no effect of the Internet on political institutions. These findings provide moderate support for the 'repression technology' perspective, and suggest that the Internet has not – at least in its first two decades of existence – contributed to a global shift towards democracy.

AbstractDoes improved communication provided by modern cellphone technology affect the rise or fall of violence during insurgencies? A priori predictions are ambiguous; introducing cellphones can enhance insurgent communications but can also make it easier for the population to share information with counterinsurgents and creates opportunities for signals intelligence collection. We provide the first systematic micro-level test of the effect of cellphone communication on conflict using data on Iraq's cellphone network (2004–2009) and event data on violence. We show that increased mobile communications reduced insurgent violence in Iraq, both at the district level and for specific local coverage areas. The results provide support for models of insurgency that focus on noncombatants providing information as the key constraint on violent groups and highlight the fact that small changes in the transaction costs of cooperating with the government can have large macro effects on conflict.

When coding events from media sources - as the majority of data projects do - different reports may oftentimes contain contradictory information. What do coders make of this? It is up to them to aggregate different reports into one coded event, and to supplement missing information based on other sources or their own background information. If not addressed properly, this may lead to a lack of replicability and to low reliability of the final data product. In this short article, we present an approach for separating (i) event reports and the information contained in them, and (ii) events, which are based on aggregate information from the reports and constitute the final data product. Our procedure preserves uncertainty arising from multiple reports and gives the user control over how missing and conflicting information should be dealt with. We illustrate our procedure with data from a current coding project, the Mass Mobilization in Autocracies Database (MMAD). [Reprinted by permission of Sage Publications Ltd., copyright holder.]

When and why ethnic groups rebel remains a central puzzle in the civil war literature. In this paper, we examine how different types of inequalities affect both an ethnic group's willingness and opportunity to fight. We argue that political and economic inter-group inequalities motivate ethnic groups to initiate a fight against the state, and that intra-group economic inequality lowers their elite's costs of providing the necessary material and/or purposive incentives to overcome collective action problems inherent to rebel recruitment. We therefore predict that internally unequal ethnic groups excluded from power and/or significantly richer or poorer relative to the country's average are most likely to engage in a civil war. To assess our claim empirically, we develop a new global measure of economic inequality by combining high-resolution satellite images of light emissions, spatial population data, and geocoded ethnic settlement areas. After validating our measure at the country- and group level, we include it in a standard statistical model of civil war onset and find considerable support for our theoretical prediction: greater economic inequality within an ethnic group significantly increases the risk of conflict, especially if political or economic inequalities between groups provide a motive.

When coding events from media sources – as the majority of data projects do – different reports may oftentimes contain contradictory information. What do coders make of this? It is up to them to aggregate different reports into one coded event, and to supplement missing information based on other sources or their own background information. If not addressed properly, this may lead to a lack of replicability and to low reliability of the final data product. In this short article, we present an approach for separating (i) event reports and the information contained in them, and (ii) events, which are based on aggregate information from the reports and constitute the final data product. Our procedure preserves uncertainty arising from multiple reports and gives the user control over how missing and conflicting information should be dealt with. We illustrate our procedure with data from a current coding project, the Mass Mobilization in Autocracies Database (MMAD).

There is an enduring interest in how geographic features influence political interactions and outcomes, and many key factors highlighted in international relations and cross-national research vary spatially within countries. Starting with the pioneering research of Richardson, we show how geographic information systems (GIS) technology and the increasing availability of spatial data can provide new opportunities to answer old and new questions. We focus on key motivations for using spatial disaggregated data and show how such data can be used in current research, drawing on examples from the study of violent conflict. Adapted from the source document.