Please wait a minute...
New Technology of Library and Information Service  2016, Vol. 32 Issue (4): 20-30    DOI: 10.11925/infotech.1003-3513.2016.04.03
Orginal Article Current Issue | Archive | Adv Search |
Identifying Influential Users in Social Networks
He Jianmin(),Yin Shu
School of Management, Hefei University of Technology, Hefei 230009, China
Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei University of Technology, Hefei 230009, China
Download: PDF(694 KB)   HTML ( 57
Export: BibTeX | EndNote (RIS)      

[Objective] This paper aims to identify the influential users in social network systems, which could help us maximize the online advertising effects. [Methods] First, we constructed the basic graphs to describe relationship among the social network system users from the perspective of social capital measurement. Second, we built the influence measurement model based on the newly constructed graphs. Finally, we identified the influential users by calculating the probabilities of users’ random browsing behaviors. [Results] The proposed method could identify users with big online influence. They were more capable of affecting others in related fields than the influential users listed by the Sina Weibo. [Limitations] The proposed method did not evaluate the impacts of user-generated contents in social network systems while measuring the users’ influence. [Conclusions] The proposed method could help business owners identify influential users in the social network system to improve the effectiveness of online advertisements.

Key wordsOnline advertisement placement      Social relationship graphs      Social capital measurements of users      Identification model of influential users     
Received: 26 October 2015      Published: 13 May 2016

Cite this article:

He Jianmin,Yin Shu. Identifying Influential Users in Social Networks. New Technology of Library and Information Service, 2016, 32(4): 20-30.

URL:     OR

[1] 何建民, 郑哲. 社交网络消费者抱怨“动机-行为”模型研究[J]. 合肥工业大学学报: 社会科学版, 2015, 29(1): 1-9.
[1] (He Jianmin, Zheng Zhe.Study of “Motivation-Behavior” Model of Consumers’ Complaints on Social Network[J]. Journal of Hefei University of Technology: Social Science, 2015, 29(1): 1-9.)
[2] O’Connor L G, Dillingham L L. Personal Experience as Social Capital in Online Investor Forums[J]. Library & Information Science Research, 2014, 36(1): 27-35.
[3] Drushel B E.HIV/AIDS, Social Capital, and Online Social Networks[J]. Journal of Homosexuality, 2013, 60(8): 1230-1249.
[4] Lin N.Social Capital: A Theory of Social Structure and Action [M]. Cambridge University Press, 2002.
[5] 唐晓波, 房小可. 融入社会关系的微博排名策略研究[J]. 现代图书情报技术, 2013(9): 74-81.
[5] (Tang Xiaobo, Fang Xiaoke.Research on Microblog Ranking Strategy with the Social Relations[J]. New Technology of Library and Information Service, 2013(9): 74-81.)
[6] Subbian K, Sharma D, Wen Z, et al.Finding Influencers in Networks Using Social Capital [C]. In: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.2013: 25-28.
[7] Zhu Z, Su J, Kong L.Measuring Influence in Online Social Network Based on the User-Content Bipartite Graph[J]. Computers in Human Behavior, 2015, 52: 184-189.
[8] Ding Z, Wang H, Guo L, et al.Finding Influential Users and Popular Contents on Twitter [C]. In: Proceedings of the 16th International Conference on Web Information System Engineering, Miami, FL, USA. Springer International Publishing, 2015: 267-275.
[9] Tang B, Lu T, Gu H, et al.Measuring Domain-Specific User Influence in Microblogs: An Actor-Network Theory Based Approach [C]. In: Proceedings of the 19th International Conference on Computer Supported Cooperative Work in Design. IEEE, 2015: 314-319.
[10] Montangero M, Furini M.TRank: Ranking Twitter Users According to Specific Topics [C]. In: Proceedings of the 12th Conference on Consumer Communications and Networking, Las Vegas, NV, USA. IEEE, 2015: 767-772.
[11] Tarokh M J, Arian H S, Speily O R B. Discovering Influential Users in Social Media to Enhance Effective Advertisement[J]. Advances in Computer Science: An International Journal, 2015, 4(5): 23-28.
[12] Liu N, Li L, Xu G, et al.Identifying Domain-Dependent Influential Microblog Users: A Post-Feature Based Approach [C]. In: Proceedings of the 28th AAAI Conference on Artificial Intelligence. AAAI, 2014: 3122-3123.
[13] Ding Z, Jia Y, Zhou B, et al.Mining Topical Influencers Based on the Multi-relational Network in Micro-blogging Sites[J]. Communications, 2013, 10(1): 93-104.
[14] 丁兆云, 周斌, 贾焰, 等. 微博中基于多关系网络的话题层次影响力分析[J]. 计算机研究与发展, 2013, 50(10): 2155-2175.
[14] (Ding Zhaoyun, Zhou Bin, Jia Yan, et al.Topical Influence Analysis Based on the Multi-Relational Network in Microblogs[J]. Journal of Computer Research and Development, 2013, 50(10): 2155-2175.)
[15] 齐超, 陈鸿昶, 于洪涛. 基于用户行为综合分析的微博用户影响力评价方法[J]. 计算机应用研究, 2014, 31(7): 2004-2007.
[15] (Qi Chao, Chen Hongchang, Yu Hongtao.Method of Evaluating Micro-blog Users’ Influence Based on Comprehensive Analysis of User Behavior[J]. Application Research of Computers, 2014, 31(7): 2004-2007.)
[16] 左文明, 王旭, 樊偿. 社会化电子商务环境下基于社会资本的网络口碑与购买意愿关系[J]. 南开管理评论, 2014 (4): 140-150.
[16] (Zuo Wenming, Wang Xu, Fan Chang.Relationship Between Electronic Word of Mouth and Purchase Intention in Social Commerce Environment: A Social Capital Perspective[J]. Nankai Business Review, 2014(4): 140-150.)
[17] Wu X, Kumar V.The Top Ten Algorithms in Data Mining[M]. Chapman and Hall/CRC, 2009.
[18] 毛佳昕, 刘奕群, 张敏, 等. 基于用户行为的微博用户社会影响力分析[J]. 计算机学报, 2014, 37(4): 791-798.
[18] (Mao Jiaxin, Liu Yiqun, Zhang Min, et al.Social Influence Analysis for Micro-blog User Based on User Behavior[J]. Chinese Journal of Computers, 2014, 37(4): 791-798.)
[19] Russell M A.Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More[M]. O’Reilly Media, 2013.
[20] Li L, Sun L, Ning G.Deterioration Prediction of Urban Bridges on Network Level Using Markov-Chain Model[J]. Mathematical Problems in Engineering, 2014, 9(1): 129-145.
No related articles found!
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938