陈毅恒,李雪婷,王 彪,刘 挺. 基于网络结构的多种用户影响力分析算法对比研究[J]. 中文信息学报, 2017, 31(4): 216-222.
CHEN Yiheng, LI Xueting, WANG Biao, LIU Ting. Comparison of User Influence Analysis Algorithms Based on Network Structure. , 2017, 31(4): 216-222.
Comparison of User Influence Analysis Algorithms Based on Network Structure
CHEN Yiheng1, LI Xueting2, WANG Biao1, LIU Ting1
1. Research Center for Social Computing and Information Retrieval of Computer Scienceand Technology School, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China; 2. Information Counseling of Library, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
Abstract:The analysis of the user influence in the social network is a key research issue in social marketing. This paper is focused on several network structure based algorithms for user influence analysis, and conducts a contrastive study on their performances.
[1] Reka Albert, Hawoong Jeong, Albert-Laszlo Barabasi. Error and attack tolerance of complex networks[J]. Nature, 2000, 406 (6794): 378-382. [2] S Wasserman, K Faust, D Iacobucci, et al. Social Network Analysis: Methods and Applications[M]. Cambridge University Press, 1994. [3] Jon M Kleinberg. Authoritative sources in a hyperlinked environment[J]. Journal of the ACM, 1999, 46(5): 604-632. [4] Lawrence Page, Sergey Brin, Rajeev Motwani, et al. The PageRank citation ranking: Bringing order to the web[J]. World Wide Web Internet and Web Information Systems, 1998, 54(2): 1-17. [5] T H Haveliwala. Topic-sensitive PageRank: a context-sensitive ranking algorithm for Web search[J]. IEEE Transactions on Knowledge and Data Engineering, 2003, 15(4): 784-796. [6] Jun Zhang, Mark S Ackerman, Lada Adamic. Community Net Simulator: Using Simulations to Study Online Community Networks[J]. Forum American Bar Association, 2007, 2005(3): 221-230. [7] Jialun Qin, Jennifer J Xu, Daning Hu, et al. Analyzing Terrorist Networks: A Case Study of the Global Salafi Jihad Network[J]. Network, 2005, 3495(196): 287-304. [8] Jennifer J Xu, Hsinchun Chen. Fighting organized crimes: using shortest-path algorithms to identify associations in criminal networks[J]. Decision Support Systems, 2004, 38(3): 473-487. [9] Meeyoung Cha, Krishna P Gummadi. Measuring User Influence in Twitter: The Million Follower Fallacy[J]. Artificial Intelligence, 2010, 146(1): 10-17. [10] Daniel M Romero, Wojciech Galuba, Sitaram Asur, et al. Influence and Passivity in Social Media[J]. Information Systems Journal, 2010, 1(4): 1-9. [11] Jianshu Weng, Ee-Peng Lim, Jing Jiang, et al. TwitterRank: Finding Topic-Sensitive Influential Twitters[C]// Proceedings of WSDM, 2010: 261-270. [12] Junming Huang, Xue-qi Cheng, Hua-wei Shen, et al. Exploring Social Influence via Posterior Effect of Word-of-Mouth Recommendations[C]//Proceedings of the 5th ACM international conference on Web search and data mining,2012: 573-582. [13] Yaron Singer. How to Win Friends and Influence People, Truthfully: Influence Maximization Mechanisms for Social Networks[C]// Proceedings of WSDM, 2012: 733-742. [14] Smriti Bhagat, Amit Goyal, Laks V S Lakshmanan. Maximizing Product Adoption in Social Networks[C]// Proceedings of the 15th ACM international conference on Web search and data mining WSDM, 2012: 603-612. [15] Meng Wang, Gang Zhou, Jun Yu Chen. Analysis of User Influence Using User Behavior and Random Walk[J]. Applied Mechanics and Materials, 2014, 571: 1163-1167. [16] Yulan Huang. Analysis of user influence in social network based on behavior and relationship[J]. Measurement, Information and Control, 2013: 682-686. [17] Bin Bi, Yuanyuan Tian et al. Scalable Topic-Specific Influence Analysis on Microblogs[C] //Proceedings of WSDM, 2014: 513-522.