Social networks and voter turnout.

This paper develops a model of voter turnout that embeds Riker and Ordeshook's (1968 Am. Pol. Sci. Rev. 62, 25-42 (doi:10.2307/1953324)) calculus of voting into the context of a social network. In the model, an individual's expressive benefits to voting depend on the behaviour of their social contacts. We show that there may be multiple equilibria and analyse how these equilibria depend on the structure of the network. We discuss six empirical implications of the model for turnout, some of which suggest novel answers to longstanding puzzles in the turnout literature, such as: why are higher income individuals more likely to vote even in cases when registration costs are low? Why is turnout so difficult to predict? Why does lowering registration costs disproportionately increase turnout among high-income voters? And why do we observe inertia in turnout across elections?

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.