Ph.D., University of Pennsylvania, Communication
M.A., University of Pennsylvania, Communication
M.A., Hebrew University of Jerusalem, Political Communication
B.A., Hebrew University of Jerusalem, Philosophy, Political Science and Economics
Political Communication, Computational Social Science, Media and Elections, International Communication, Misinformation
Dr. Walter’s research is centered on the intersection between classic media effects theories, and novel computational social sciences methods. His research addresses the ways computational methods such as network analysis, topic modeling, and supervised machine learning can aid in the understanding of various political communication processes, with emphasis on election campaigns, international conflicts, the representation of foreign countries in news and entertainment media, online misinformation campaigns, and political extremism.
Among his current and recent research projects are: creating unsupervised machine learning approaches to frame analysis of traditional mass media and social media content (ANTMN), the role of discourse structure in shaping public opinion, the conceptualization, measurement and impact of thematic diversity, strategies of political candidates on twitter, impact of news framing on candidates electoral success, the impact of foreign actors’ online interference in US politics, and Far right extremism in online platforms.
Walter, D. and Ophir, Y. (2019) The Elephant and the Bird: Republican Candidates’ Use of Strategy and Issue Framing in Twitter During the 2016 Republican Presidential Primaries. The International Journal of Communication. https://doi.org/1932–8036/20190005. (https://doi.org/1932%E2%80%938036/20190005) https://ijoc.org/index.php/ijoc/article/view/11808 ( (https://ijoc.org/index.php/ijoc/article/view/11808) https://ijoc.org/index.php/ijoc/article/view/11808) (https://ijoc.org/index.php/ijoc/article/view/11808)
* Walter, D. and Ophir, Y. (2019) News Frame Analysis: An Inductive Mixed-Method Computational Approach. Communication Methods and Measures. http://dx.doi.org/10.1080/19312458.2019.1639145. (http://dx.doi.org/10.1080/19312458.2019.1639145) https://www.tandfonline.com/doi/full/10.1080/19312458.2019.1639145 ( (https://www.tandfonline.com/doi/full/10.1080/19312458.2019.1639145) https://www.tandfonline.com/doi/full/10.1080/19312458.2019.1639145) (https://www.tandfonline.com/doi/full/10.1080/19312458.2019.1639145)
* Walter, D. (2019). Exploring Thematic Diversity In News Coverage And Social Media Activity Of Political Candidates Using Unsupervised Machine Learning. University of Pennsylvania, Philadelphia PA. https://repository.upenn.edu/dissertations/AAI10841639/ ( (https://repository.upenn.edu/dissertations/AAI10841639/) https://repository.upenn.edu/dissertations/AAI10841639/) (https://repository.upenn.edu/dissertations/AAI10841639/)
* Walter, D., Sheafer, T., Nir, L. & Shenhav R. S. (2016) Not All Countries are Created Equal: Foreign Countries Prevalence in US News and Entertainment Media. Mass Communication and Society, 19, 522-541. https://doi.org/10.1080/15205436.2016.1170853. (https://doi.org/10.1080/15205436.2016.1170853) https://www.tandfonline.com/doi/full/10.1080/15205436.2016.1170853 ( (https://www.tandfonline.com/doi/full/10.1080/15205436.2016.1170853) https://www.tandfonline.com (https://www.tandfonline.com/doi/full/10.1080/15205436.2016.1170853)