Identifying Weibo Opinion Leaders with Social Network Analysis and Influence Diffusion Model
Chen Fen(), Fu Xi, He Yuan, Xue Chunxiang
School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China The Priority Academic of Jiangsu Higher Education Institutions, Nanjing 210094, China
[Objective] This paper tries to identify Weibo opinion leaders with the help of social network analysis and influence diffusion model. [Methods] First, we analyzed the opinion leaders’ characteristics based on the social network analysis. Then we optimized the existing influence diffusion model from the perspectives of impact scope and extent. Finally, we applied the new model to find opinion leaders. [Results] Compared with the models built on centrality analysis or semantic similarity, the optimized model obtained better ranking for opinion leaders, which was consistent with the Weibo data. [Limitations] Only examined the proposed method with data on GMO foods. [Conclusions] The proposed model could effectively identify the Weibo opinion leaders.
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