“Horizontal” Two-Step Flow: The Role of Opinion Leaders in Directing Attention to Social Movements in Decentralized Information Environments

ABSTRACTThe increasing ubiquity of online social networking sites has brought with it questions as to whether old models of communication flows—specifically, the two-step flow model—have potential explanatory power in an era when individuals can follow politicians, celebrities, and other opinion leaders. We expand research using two-step flow to explain attention in the new media ecology by accounting for what we term horizontal two-step flow, wherein non-media actors leverage the influence of online opinion leaders, who may include traditional news media actors, to attract attention to their messages. Using the political fight over repeal of the Eighth Amendment of the Irish Constitution, we examine engagement with communication messages from pro- and anti-repeal organizations in the country, demonstrating that the horizontal two-step flow model of communication explains attention to social movement organizations. In particular, we find that opinion leaders—those with high social influence on Twitter, either via verified status or high degree centrality—increase the diffusion of social movement messages beyond movements’ social media follower bases. Disclosure statementNo potential conflict of interest was reported by the authors.Notes1 Note that at the time of researching and writing this manuscript Twitter limited the number of historical tweets pulled to 3,200, but since then has made the historical archive available to academic researchers. However, because our data include not only tweets but follower/following behavior, we did not increase the sample size because we would not have been able to include those parameters in the updated dataset.2 We also tested these relationships using the count of non-following retweets and found very similar results. However, given that the number of overall retweets is likely confounded with the number of retweets by non-following accounts—e.g., higher retweet volume likely begets higher non-following retweet volume—we chose instead to operationalize our dependent variable as the proportion of retweets posted by non-following accounts.Additional informationNotes on contributorsKate HuntKate Hunt is a Lecturer in International Studies in the Hamilton Lugar School of Global and International Studies at Indiana University. Her research focuses on the intersections of political communication, social movements, and gender issues.Mike GruszczynskiMike Gruszczynski is an Assistant Professor of Communication Science in The Media School at Indiana University. He specializes in agenda-setting, studies of the media ecology, and public opinion.