Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/64820


Title: Discovering Leaders from Social Network by Action Cascade
Authors: Tsai, Ming-Feng;Tzeng, Chih-Wei;Lin, Zhe-Li;Chen, Arbee L. P.
蔡銘峰
Contributors: 資科系
Keywords: Social Network Analysis;Path Mining;Opinion Leader Discovery
Date: 2014
Issue Date: 2014-03-21 17:46:46 (UTC+8)
Abstract: This paper proposes an approach to discovering community leaders in social network by means of a probabilistic time-based graph propagation model. To conduct the approach, we define an exponential decay function for influence as a function of time, and build action-specific influence chains by multiplying path propagation values; then, we create general influence chains by normalizing over all possible actions. In the study, our approach identifies community leaders as those people whose initiated influence chains are relatively more than the chains they involved. In our experiments, a small Facebook network dataset with 134 nodes and 517 edges is employed to assess the performance of the proposed method. In addition, several baselines are also carried out for comparison, including three naive and one user-involved approaches. The experimental results show that, compared with the baselines, the proposed method can effectively identify community leaders within the social network, achieving 0.8 in terms of F-measure.
Relation: Social Network Analysis and Mining,Proceedings of the Fifth Workshop on Social Network Systems
Data Type: article
DOI 連結: http://dx.doi.org/10.1145/2181176.2181188
Appears in Collections:[資訊科學系] 期刊論文

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