The Evaluation of the Social Network’s Nodes Influence Based on Users’ Behavior
Humanities and Social Sciences
Volume 3, Issue 5, September 2015, Pages: 234-239
Received: Nov. 18, 2015; Published: Nov. 18, 2015
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Authors
Fudong Wang, Gloria Sun Business School, Donghua University, Shanghai, China
Pei Wang, Gloria Sun Business School, Donghua University, Shanghai, China
Sunzeng Yao, Postgraduate Department, Donghua University, Shanghai, China
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Abstract
How to effectively identifying opinion leaders has become a hot research point. It’s essence is to identify the nodes with the strong influence in social network. This paper analyzes the behaviors of users in social networks and proposes the impact evaluation algorithm based on multi-angle user behaviors which is User-Activity Rank algorithm. The algorithm uses the basic idea of PageRank algorithm, considers user’s creativity, interactivity and content quality and designs the uneven distribution mechanism between the users’ UA Rank value, making the computation nodes more accurate. This paper uses Car Home Forum Case for analysis and finds that this algorithm can be more accurate and objective. User-Activity Rank algorithm can help companies improve the accuracy of identifying opinion leaders and promote network marketing with their influence.
Keywords
Social Network, Opinion Leaders, PageRank, Users’ Behavior
To cite this article
Fudong Wang, Pei Wang, Sunzeng Yao, The Evaluation of the Social Network’s Nodes Influence Based on Users’ Behavior, Humanities and Social Sciences. Vol. 3, No. 5, 2015, pp. 234-239. doi: 10.11648/j.hss.20150305.21
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