Understanding the Political Ideology of Legislators from Social Media Images

In this paper, we seek to understand how politicians use images to express ideological rhetoric through Facebook images posted by members of the U.S. House and Senate. In the era of social media, politics has become saturated with imagery, a potent and emotionally salient form of political rhetoric which has been used by politicians and political organizations to influence public sentiment and voting behavior for well over a century. To date, however, little is known about how images are used as political rhetoric. Using deep learning techniques to automatically predict Republican or Democratic party affiliation solely from the Facebook photographs of the members of the 114th U.S. Congress, we demonstrate that predicted class probabilities from our model function as an accurate proxy of the political ideology of images along a left-right (liberal-conservative) dimension. After controlling for the gender and race of politicians, our method achieves an accuracy of 59.28% from single photographs and 82.35% when aggregating scores from multiple photographs (up to 150) of the same person. To better understand image content distinguishing liberal from conservative images, we also perform in-depth content analyses of the photographs. Our findings suggest that conservatives tend to use more images supporting status quo political institutions and hierarchy maintenance, featuring individuals from dominant social groups, and displaying greater happiness than liberals.Comment: To appear in the Proceedings of International AAAI Conference on Web and Social Media (ICWSM 2020

Replication Data for: Longitudinal Network Centrality Using Incomplete Data

How does individuals’ influence in a large social network change? Social scientists have difficulty answering this question because measuring influence requires frequent observations of a population of individuals’ connections to each other, while sampling that social network removes information in a way that can bias inferences. This paper introduces a method to measure influence over time accurately from sampled network data. Ranking individuals by the sum of their connections’ connections — neighbor cumulative indegree centrality — preserves the rank influence ordering that would be achieved in the presence of complete network data, lowering the barrier to measuring influence accurately. The paper then shows how to measure that variable changes each day, making it possible to analyze when and why an individual’s influence in a network changes. This method is demonstrated and validated on 21 Twitter accounts in Bahrain and Egypt from early 2011. The paper then discusses how to use the method in domains such as voter mobilization and marketing

PREDICTABILITY VERSUS FLEXIBILITY Secrecy in International Investment Arbitration

There is heated debate over the wisdom and effect of secrecy in international negotiations. This debate has become central to the process of foreign investment arbitration because parties to disputes nearly always can choose to hide arbitral outcomes from public view. Working with a new database of disputes at the world's largest investor-state arbitral institution, the World Bank's International Centre for Settlement of Investment Disputes, the authors examine the incentives of firms and governments to keep the details of their disputes secret. The authors argue that secrecy in the context of investment arbitration works like a flexibility-enhancing device, similar to the way escape clauses function in the context of international trade. To attract and preserve investment, governments make contractual and treaty-based promises to submit to binding arbitration in the event of a dispute. They may prefer secrecy in cases when they are under strong political pressure to adopt policies that violate international legal norms designed to protect investor interests. Investors favor secrecy when managing politically sensitive disputes over assets they will continue to own and manage in host countries long after the particular dispute has passed. Although governments prefer secrecy to help facilitate politically difficult bargaining, secrecy diminishes one of the central purposes of arbitration: to allow governments to signal publicly their general commitment to investor-friendly policies. Understanding the incentives for keeping the details of dispute resolution secret may help future scholars explain more accurately the observed patterns of wins and losses from investor-state arbitration as well as patterns of investment

Mask images on Twitter increase during COVID-19 mandates, especially in Republican counties

Wearing masks reduces the spread of COVID-19, but compliance with mask mandates varies across individuals, time, and space. Accurate and continuous measures of mask wearing, as well as other health-related behaviors, are important for public health policies. This article presents a novel approach to estimate mask wearing using geotagged Twitter image data from March through September, 2020 in the United States. We validate our measure using public opinion survey data and extend the analysis to investigate county-level differences in mask wearing. We find a strong association between mask mandates and mask wearing-an average increase of 20%. Moreover, this association is greatest in Republican-leaning counties. The findings have important implications for understanding how governmental policies shape and monitor citizen responses to public health crises