Attribution of responsibility and blame are important topics in political science especially as individuals tend to think of political issues in terms of questions of responsibility, and as blame carries far more weight in voting behavior than that of credit. However, surprisingly, there is a paucity of studies on the attribution of responsibility and blame in the field of disaster research. In this work, we investigate the attribution of responsibility and blame through social media in the case of Flint water crisis. We form hypotheses based on social scientific theories in disaster research and then operationalize them on public responses available on social media rather than employing traditional data collection methods such as interviewing and surveying. In particular, we investigate the source for blame, the partisan predisposition, the concerned geographies, and the contagion of complaining by testing our hypotheses on data collected from Twitter. Our results demonstrate the utility of social media data in testing those hypotheses, which are rooted in sociology of disasters. Our findings are not only aligned with official reports listing the responsible officials for the source blame, but also reveal a partisan predisposition in regards to Democratic and Republican stances. We also confirm that closer geographies are more concerned and complaining seems contagious in social media conversations. This paper adds to the sociology of disasters research by exploiting a new, rarely used data source (the social web), and by employing new computational methods (such as sentiment analysis and retrospective cohort study design) on this new form of data. In this regard, this work can be seen as the first step toward drawing more challenging inferences on the sociology of disasters from "big social data".

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