A User Influence Strength Model in E-commerce Social Networks Based on Closeness and Users?? Credit
Ju Chunhua1,2, Zhao Kaidi2, Bao Fuguang1,2
1. Department of Modern Business Research Center, Zhejiang Gongshang University, Hangzhou 310018 2. School of Management Science & Engineering, Zhejiang Gongshang University, Hangzhou 310018
琚春华, , 赵凯迪, 鲍福光,. 融入紧密度中心性与信用的社交网络用户影响力强度计算模型[J]. 情报学报, 2019, 38(2): 170-177.
Ju Chunhua, Zhao Kaidi, Bao Fuguang. A User Influence Strength Model in E-commerce Social Networks Based on Closeness and Users?? Credit. 情报学报, 2019, 38(2): 170-177.
[1] 樊兴华, 赵静, 方滨兴, 等. 影响力扩散概率模型及其用于意见领袖发现研究[J]. 计算机学报, 2013, 36(2): 360-367. [2] Lazarsfeld P F, Berelson B, Gaudet H. The people’s choice[J]. Eco-Architecture: Harmonisation between Architecture and Nature, 1944, 18(1): 154. [3] Aral S, Walker D. Identifying influential and susceptible members of social networks[J]. Science, 2012, 337(6092): 337. [4] 马茜, 马军. 在影响力最大化问题中寻找种子节点的替补节点[J]. 计算机学报, 2017, 40(3): 674-686. [5] Goyal A, Bonchi F, Lakshmanan L V S. Learning influence probabilities in social networks[C]// Proceedings of the Third International Conference on Web Search and Web Data Mining. New York: ACM Press, 2010: 241-250. [6] Tang J, Sun J M, Wang C, et al. Social influence analysis in large-scale networks[C]// Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM Press, 2009: 807-816. [7] Page L, Brin S, Motwani R, et al. The PageRank citation ranking: Bringing order to the Web[R]. Stanford University, 1998. [8] Weng J, Lim E P, Jiang J, et al. TwitterRank: finding topic-sensitive influential twitterers[C]// Proceedings of the ACM International Conference on Web Search and Data Mining. New York: ACM Press, 2010: 261-270. [9] Kleinberg J M. Authoritative sources in a hyperlinked environment[J]. Journal of the ACM, 1999, 46(5): 604-632. [10] Cha M, Haddadi H, Benevenuto F, et al. Measuring user influence in Twitter: The million follower fallacy[C]// Proceedings of the International Conference on Weblogs and Social Media. Palo Alto: AAAI Press, 2010. [11] Brandes U. A faster algorithm for betweenness centrality[J]. The Journal of Mathematical Sociology, 2001, 25(2): 163-177. [12] Zhang Y C, Liu Y, Cheng H, et al. A method of measuring user influence in MicroBlog[J]. Journal of Convergence Information Technology, 2011, 6(10): 243-250. [13] 顾洁, 胡安安, 刘旭, 等. 社交网络正、负影响力计算——基于符号网络的PageRank算法改进[J]. 情报学报, 2015, 34(7): 725-733. [14] 何军, 刘业政. 基于社交关系和影响力的在线社交网络用户兴趣偏好获取方法研究[J]. 情报学报, 2014, 33(7): 730-739. [15] 司夏萌, 刘云. 虚拟社区中人际交互行为的统计分析研究[J]. 物理学报, 2011, 60(7): 859-866. [16] Katz E, Lazarsfeld P F, Roper E. Personal influence: the part played by people in the flow of mass communications[J]. American Journal of Sociology, 1956, 62(1): 1583-1583. [17] 李阅志, 祝园园, 钟鸣. 基于k-核过滤的社交网络影响最大化算法[J]. 计算机应用, 2018, 38(2): 464-470. [18] 周飞, 高茂庭. 基于PageRank的网络社区意见领袖发现算法[J]. 计算机工程, 2018, 44(2): 203-209. [19] Freeman L C. Centrality in social networks conceptual clarification[J]. Social Networks, 1979, 1(3): 215-239.