Digital Society Project Working Papers provide an outlet for exciting new research on the intersection of the internet and politics. If you use DSP data in your work and would like to contribute a working paper to the series, please let us know here!
DSP Working Paper #1: Introducing the Digital Society Project
With this working paper we introduce a new project—the Digital Society Project (DSP)–which aims to answer some of the most important questions surrounding the intersection of the internet and politics. We introduce the DSP dataset, the product of a global survey of hundreds of country and area experts, and preview key descriptive patterns from this data collection effort. The data covers virtually all countries in the world from 2000 to 2018 and measures a set of 35 new indicators of polarization and politicization of social media, misinformation campaigns and coordinated information operations, and foreign influence in and monitoring of domestic politics. We expect that the data and the research produced by this project will be of great interest to both the academic and policy communities, at a time when understanding the political and social consequences of the internet is rapidly increasing.
DSP Working Paper #2: #MeToo, Gender Norms and the 2018 Mid-Term Elections on Twitter
How do gender norms drive candidate behavior in the #MeToo era? We investigate how previously established gender stereotypes played out on Twitter during the 2018 U.S. elections. We show that female candidates focused more on covering ‘women’s issues’ such as health-care, while male candidates – on the traditional ‘male issues’ such as the economy. The age of the candidates, the level of gender equality in electoral districts, and the presence of other women as candidates interacts with the extent to which there is a gender gap in the topics covered by candidates. Second, we find that female candidates are more aggressive on Twitter, and this is not driven by them being newcomers. Finally, we examine whether stereotypes affect women’s electoral performance and the likelihood of being harassed online by the public. Talking about male issues decreases the likelihood of women being elected but it does not increase the likelihood of being targeted by angry speech online. Tweeting angrily is also a significant predictor of being elected but female candidates who use angry speech on Twitter, are more likely to receive tweets with abusive language, in particular by other women.