Do images affect online political mobilization? If so, how? These questions are of fundamental importance to scholars of social movements, contentious politics, and political behavior generally. However, little prior work has systematically addressed the role of images in mobilizing online participation in social movements. We first confirm that images have a positive mobilizing effect in the context of online protest activity. We then argue that images are mobilizing because they trigger stronger emotional reactions than text. Building on existing political psychology models, we theorize that images evoking enthusiasm, anger, and fear should be particularly mobilizing, while sadness should be demobilizing. We test the argument through a study of Twitter activity related to a Black Lives Matter protest. We find that both images in general and some of the proposed emotional attributes (enthusiasm and fear) contribute to online participation. The results hold when controlling for alternative theoretical mechanisms for why images should be mobilizing, and for the presence of frequent image features. Our paper provides evidence supporting the broad argument that images increase the likelihood of a protest to spread online while teasing out the mechanisms at play in a new media environment.

Video advertisements, either through television or the Internet, play an essential role in modern political campaigns. For over two decades, researchers have studied television video ads by analyzing the hand-coded data from the Wisconsin Advertising Project and its successor, the Wesleyan Media Project (WMP). Unfortunately, manually coding more than a hundred of variables, such as issue mentions, opponent appearance, and negativity, for many videos is a laborious and expensive process. We propose to automatically code campaign advertisement videos. Applying state-of-theart machine learning methods, we extract various audio and image features from each video file. We show that our machine coding is at least as accurate as human coding for many variables of the WMP data sets. Since many candidates make their advertisement videos available on the Internet, automated coding can dramatically improve the efficiency and scope of campaign advertisement research.

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Agenda setting and issue framing research investigates how frames impact public attention, policy decisions, and political outcomes. Social media sites, such as Twitter, provide opportunities to study framing dynamics in an important area of political discourse. We present a method for identifying frames in tweets and measuring their effectiveness. We use topic modeling combined with manual validation to identify recurrent problem frames and topics in thousands of tweets by gun rights and gun control groups following the Marjory Stoneman Douglas High School in Parkland, Florida, shooting. We find that each side used Twitter to advance policy narratives about the problem in Parkland. Gun rights groups' narratives implied that more gun restrictions were not the solution. Their most effective frame focused on officials' failures to enforce existing laws. In contrast, gun control groups portrayed easy access to guns as the problem and emphasized the importance of mobilizing politically to force change.

The demographic composition of Kazakhstan after the fall of the Soviet Union presented a dilemma to the new Kazakhstani government: Should it advance a Kazakh identity as paramount, possibly alienating the large non-Kazakh population? Or should it advocate for a non-ethnicized national identity? How would those decisions be made in light of global norms of liberal multiculturalism? And, critically, would citizens respond to new frames of identity? This paper provides an empirical look at supraethnic identity-building in Kazakhstan – that is, at the development of a national identity that individuals place above or alongside their ethnic identification. We closely examine the Assembly of People of Kazakhstan to describe how Kazakhstani policies intersect with theories of nationalism and nation-building. We then use ordered probit models to analyze data from a 2014 survey to examine how citizens of Kazakhstan associate with a “Kazakhstani” supraethnic identity. Our findings suggest that despite the Assembly of People's rhetoric, there are still significant barriers to citizen-level adoption of a supraethnic identity in Kazakhstan, particularly regarding language. However, many individuals do claim an association with Kazakhstani identity, especially those individuals who strongly value citizenship in the abstract.

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Contemporary dictators routinely co-opt institutions crucial for democratic governance. Although an extensive literature examines why and how aspiring autocrats bring elections and parties under their control, constitutions—and the judicial or quasi-judicial bodies charged with interpreting constitutions—are often assumed to reflect the existing balance of power. But following regime change, constitutional courts’ power of review makes them integral for establishing political supremacy. We detail how President Nursultan Nazarbayev of Kazakhstan captured the Constitutional Court via its transformation into the Constitutional Council. The uncertainty and upheaval of the post-Soviet collapse created opportunities for formal institutional changes that made the court susceptible to executive capture. Nazarbayev subsequently used the council rulings to lay claim to democratic and constitutional legitimacy in a clear example of authoritarian constitutionalism. To trace the process of capture and legitimation, we examine key court rulings throughout the president’s tenure using a database of Constitutional Council decisions.