Abstract
Using 414,322 tweets drawn from 143,404 individual Twitter users located in all 435 U.S. congressional districts, this study employed big data and automated content analysis techniques to explore the degree to which socioeconomic status (SES), social capital potential (the degree to which a congressional district has the potential for interconnected citizen networks), and in-district partisan polarization were associated with incivility on Twitter during the 2012 presidential election. Broadly speaking, and with some exceptions, the results indicated that election oriented incivility on Twitter was highest in districts that had low SES indicators, low levels of social capital potential, and low levels of partisan polarity. In its sum, this study shows how large social data sets (i.e., the Census) can be combined with big data to explain social phenomena.
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