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Abstract Interstate compacts are formal structures through which multiple states work together towards a common goal or shared agenda. Previous research on compacts focuses almost exclusively on the decision to join the compact, leaving questions on post‐formation diffusion patterns unexplored. We use a unique case of three interstate compacts that form simultaneously around the same issue—the COVID‐19 pandemic—to test how policy diffuses within compacts. We employ a novel diffusion methodology, network event history analysis (NEHA), to determine the role of compact membership in policy activity. We find that compact member states are no more active in adopting policy than non‐members, but that non‐member states use compacts to free ride when making their own adoption choices. We find that compacts serve to establish members as leaders, as non‐members' policy adoptions are strongly driven by the adoptions of compact members. We also find COVID‐19 policy diffusion to be strongly driven by state ideology. 

Abstract Many types of civil unrest, including protest, violent conflict, and rebellion, have been found to be subject to both inter- and intra-state contagion. These spillover effects are conventionally tested through the application of parametric structural models that are estimated using observational data. Drawing on research in methods for network analysis, we note important challenges in conducting causal inference on contagion effects in observational data. We review a recently developed non-parametric test—the “split-halves test”—that is robust to confounding and apply the test to replication data from several recent studies in which researchers tested for contagion in civil unrest. We find that about half the time findings in the published literature fail to replicate with the split-halves test. Across ten total replications, we do not see strong patterns in terms of which results do and do not replicate. We do, however, find evidence for general contagion in six of the replications, indicating that contagion is a prevalent phenomenon in civil unrest. As such, we recommend that researchers (1) use the split-halves test as a general-purpose robustness check for parametric models of contagion in the study of civil unrest, and (2) consider modeling contagion in research on civil unrest. 

A significant body of research is dedicated to developing language models that can detect various types of online abuse, for example, hate speech, cyberbullying. However, there is a disconnect between platform policies, which often consider the author's intention as a criterion for content moderation, and the current capabilities of detection models, which typically lack efforts to capture intent. This paper examines the role of intent in the moderation of abusive content. Specifically, we review state-of-the-art detection models and benchmark training datasets to assess their ability to capture intent. We propose changes to the design and development of automated detection and moderation systems to improve alignment with ethical and policy conceptualizations of these abuses. 

Elected officials have privileged roles in public communication. In contrast to national politicians, whose posting content is more likely to be closely scrutinized by a robust ecosystem of nationally focused media outlets, sub-national politicians are more likely to openly disseminate harmful content with limited media scrutiny. In this paper, we analyze the factors that explain the online visibility of over 6.5K unique state legislators in the US and how their visibility might be impacted by posting low-credibility or uncivil content. We conducted a study of posting on Twitter and Facebook (FB) during 2020-21 to analyze how legislators engage with users on these platforms. The results indicate that distributing content with low-credibility information attracts greater attention from users on FB and Twitter for Republicans. Conversely, posting content that is considered uncivil on Twitter receives less attention. A noticeable scarcity of posts containing uncivil content was observed on FB, which may be attributed to the different communication patterns of legislators on these platforms. In most cases, the effect is more pronounced among the most ideologically extreme legislators. Our research explores the influence exerted by state legislators on online political conversations, with Twitter and FB serving as case studies. Furthermore, it sheds light on the differences in the conduct of political actors on these platforms. This study contributes to a better understanding of the role that political figures play in shaping online political discourse.