Abstract

This study finds support for agenda melding and further validates the Network Agenda Setting (NAS) model through a series of computer science methods with large datasets on Twitter. The results demonstrate that during the 2012 U.S. presidential election, distinctive audiences “melded” agendas of various media differently. “Vertical” media best predicted Obama supporters’ agendas on Twitter whereas Romney supporters were best explained by Republican “horizontal” media. Moreover, Obama and Romney supporters relied on their politically affiliated horizontal media more than their opposing party’s media. Evidence for findings are provided through the NAS model, which measures the agenda-setting effect not in terms of issue frequency alone, but also in terms of the interconnections and relationships issues inside of an agenda. doi:10.1111/jcom.12089 Big Data and computer science methods can further the findings of agenda-setting theory. Using Twitter, ap opular microblogging service, we show how supporters of Barack Obama and supporters of Mitt Romney reacted to different media agendas during the 2012 U.S. presidential election. We do so using a network analysis perspective, which shows how issues from the election were talked about in relationship to each other. The results give us a clear, large-scale picture of how the media influenced different audiences. We also offer updates to the emerging theory of agenda melding and the Network Agenda Setting (NAS) model. We have arrived at these conclusions by utilizing several computer science methods, including automated data mining and aggregation, sentiment analysis, network analysis, machine learning, and computer-assisted content analysis. Why Twitter data? In a world of social media, Twitter differentiates itself in two ways: Its messages are public and short. The majority of this data is open for all to examine (Vieweg, 2010).

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