Echo Chamber or Public Sphere? Predicting Political Orientation and Measuring Political Homophily in Twitter Using Big Data

  • Colleoni E
  • Rozza A
  • Arvidsson A
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This paper investigates political homophily on Twitter. Using a combination of machine learning and social network analysis we classify users as Democrats or as Republicans based on the political content shared. We then investigate political homophily both in the network of reciprocated and nonreciprocated ties. We find that structures of political homophily differ strongly between Democrats and Republicans. In general, Democrats exhibit higher levels of political homophily. But Republicans who follow official Republican accounts exhibit higher levels of homophily than Democrats. In addition, levels of homophily are higher in the network of reciprocated followers than in the nonreciprocated network. We suggest that research on political homophily on the Internet should take the political culture and practices of users seriously. © 2014 International Communication Association.

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  • Elanor Colleoni

  • Alessandro Rozza

  • Adam Arvidsson

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