New media platforms such as Twitter allow users to choose from a wide range of pol- itical information sources including traditional media, politicians, bloggers and other Twitter users. This study extends the theory of channel complementarity by considering the complementary selection of information sources that occur within a single social media space. This study also conceptualizes information seeking as a social network created by follow relationships on Twitter, allowing tracking actual patterns of source selection.We applied this theoretical and methodological framework to examine infor- mation seeking on Twitter related to four US gubernatorial races. We identified the main types of highly followed accounts (i.e. information hubs). Traditional news media outlets (national and local) accounted for nearly half of the information hubs, and grassroots sources such as activists and other users accounted for nearly a third. The patterns of follow relationships indicated local and national subgroups (i.e. clusters) of users identified based on network topology. Local clusters included a subgroup of more densely interconnected users in which local news media and pol- itical candidates were hubs. National clusters included a subgroup of more sparsely interconnected users in which national media and online-only news sources served as hubs. High-density clusters were also more likely to host information sources that exhibited two-way information flow with other users, while low-density clusters preferred hubs that follow traditional one-to-many information flow. Theoretical and practical implications for news media and political candidates are discussed.
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