Sub‐national governments across the United States implement a variety of policies to address large societal problems and needs. Many policies are picked up or adopted in other states. This process is called policy diffusion and allows researchers to analyse and compare the social, political, and contextual characteristics that lead to adopting certain policies, as well as the efficacy of these policies once adopted. In this paper, we introduce PDViz, a visual analytics approach that allows social scientists to dynamically analyse the policy diffusion history and underlying patterns. It is designed for analysing and answering a list of research questions and tasks posed by social scientists in prior work. To evaluate our system, we present two usage scenarios and conduct interviews with domain experts in political science. The interviews highlight that PDViz provides the result of policy diffusion patterns that align with their domain knowledge as well as the potential to be a learning tool for students to understand the concept of policy diffusion.
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Nayeem, Abdullah-Al-Raihan ; Elshambakey, Mohammed ; Dobbs, Todd ; Lee, Huikyo ; Crichton, Daniel ; Zhu, Yimin ; Chokwitthaya, Chanachok ; Tolone, William J. ; Cho, Isaac ( , 2021 IEEE International Conference on Big Data (Big Data))
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Bhattacharjee, Sreyasee Das ; Tolone, William J. ; Mahabal, Ashish ; Elshambakey, Mohammed ; Cho, Isaac ; Nayeem, Abdullah al-Raihan ; Yuan, Junsong ; Djorgovski, George ( , IEEE International Conference on Big Data)