Abstract
ABSTRACTThis study examined the echo chamber phenomenon and opinion leadership on Twitter based on the 2016 U.S. presidential election. Network analysis and ‘big data’ analytics were employed to analyze more than 50 million tweets about the two presidential candidates, Donald Trump and Hillary Clinton, during the election cycle. Overall, the results suggested that Twitter communities discussing Trump and Clinton differed significantly in the level of political homogeneity and opinion leadership, and that certain opinion leaders were responsible of creating homogeneous communities on Twitter. This study made a theoretical contribution to the literature by linking opinion leadership and Twitter’s network structure and shedding light on what may have caused the echo chamber problem to happen in an emerging media landscape.
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