Predicting Opinion Leaders in Twitter Activism Networks: The Case of the Wisconsin Recall Election

Title
Predicting Opinion Leaders in Twitter Activism Networks: The Case of the Wisconsin Recall Election
Author(s)
박한우Weiai Wayne Xu[Weiai Wayne Xu]Yoonmo Sang[Yoonmo Sang]Stacy Blasiola[Stacy Blasiola]
Keywords
SOCIAL NETWORKS; SOUTH-KOREA; ONLINE; COMMUNICATION; DISCUSSIONS; INVOLVEMENT; POLITICIANS; NEWS; FLOW
Issue Date
201409
Publisher
SAGE PUBLICATIONS INC
Citation
AMERICAN BEHAVIORAL SCIENTIST, v.58, no.10, pp.1278 - 1293
Abstract
This study employs content and network analysis techniques to explore the predictors of opinion leadership in a political activism network on Twitter. The results demonstrate the feasibility of using user-generated content to measure user characteristics. The characteristics were analyzed to predict users' performance in the network. According to the results, Twitter users with higher connectivity and issue involvement are better at influencing information flow on Twitter. User connectivity was measured by betweenness centrality, and issue involvement was measured by a user's geographic proximity to a given event and the contribution of engaging tweets. In addition, the results show that tweets by organizations had greater influence than those by individual users.
URI
http://hdl.handle.net/YU.REPOSITORY/30914http://dx.doi.org/10.1177/0002764214527091
ISSN
0002-7642
Appears in Collections:
문과대학 > 언론정보학과 > Articles
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