Barbera, P., Casas Salleras, A., Nagler, J., Egan, P., Bonneau, R., Jost, J., & Tucker, J. (2019). Who leads? Who follows? Measuring issue attention and agenda setting by legislators and the mass public using social media data. American Political Science Review, 113(4), 883-901.
Casas Salleras, A., & Webb Williams, N. (2019). Images that matter: Online protests and the mobilizing role of pictures. Political Research Quarterly, 72, 360-375. https://doi.org/10.1177/1065912918786805
Casas Salleras, A., Denny, M., & Wilkerson, J. (2019). More effective than we thought: Accounting for legislative hitchhikers reveals a more inclusive and productive lawmaking process. American Journal of Political Science. https://doi.org/10.1111/ajps.12472
Webb Williams, N., Casas Salleras, A., & Wilkerson, J. (Accepted/In press). An introduction to images as data for social science research: Convolutional neural nets for image classification. Cambridge University Press.
Suarez, D., Husted, K., & Casas Salleras, A. (2018). Community foundations as advocates: Social change discourse in the philanthropic sector. Interest Groups & Advocacy, 7, 206-232.
Wilkerson, J., & Casas Salleras, A. (2017). Large-scale computerized text analysis in political science: Opportunities and challenges. Annual Review of Political Science, 20, 529-544.
Casas Salleras, A., Davesa, F., & Congosto, M. (2016). Media coverage of a “connective” action: The interaction between the 15-M movement and the mass media. Revista española de investigaciones sociológicas, 155. https://doi.org/10.5477/cis/reis.155.73
Casas Salleras, A. (2019). CQ Press Award for Best paper on legislative politics.
Talk / presentation
Casas Salleras, A. (speaker) (1-8-2019). Lecture at the summer school in computational social science 2019, Introduction to Computer Vision for Social Science Research, Berlin, Germany.