WANG Nan, SUN Qindong, ZHOU Yadong, SHEN Si. A Study on Influential User Identification in Online Social Networks[J]. Chinese Journal of Electronics, 2016, 25(3): 467-473. doi: 10.1049/cje.2016.05.012
Citation: WANG Nan, SUN Qindong, ZHOU Yadong, SHEN Si. A Study on Influential User Identification in Online Social Networks[J]. Chinese Journal of Electronics, 2016, 25(3): 467-473. doi: 10.1049/cje.2016.05.012

A Study on Influential User Identification in Online Social Networks

doi: 10.1049/cje.2016.05.012
Funds:  This work is supported by the National Natural Science Foundation of China (No.61172124, No.61571360, No.61202392).
More Information
  • Corresponding author: SUN Qindong was born in 1975. He is now the professor in the Department Computer Science and Engineering of Xi'an University of Technology. His research interests include network information security, online social networks and web of things. (Email:
  • Received Date: 2015-07-06
  • Rev Recd Date: 2015-12-07
  • Publish Date: 2016-05-10
  • Influential user evaluation is great importance in many application areas of online social networks. In order to identify influential users in a more adequate and practical way, we propose a Dynamic regional interaction model (DRI) to evaluate user influence in online social networks. Influential users can be identified by the influence effect on different distance users based on dynamic regional interaction model. We have applied the influential user identification method to Sina Weibo and the experimental results show that compared with the existing methods the proposed method can identify the influence users in a more accuracy and efficiency way.
  • loading
  • C. Wang, X.Y. Yang, K. Xu, et al., "SEIR-Based model for the information spreading over SNS", Chinese Journal of Electronics, Vol.42, No.11, pp.2325-2330, 2014.
    G.Z. Dong, R.G. LI and W. Yang, "Microblog burst keywords detection based on social trust and dynamics model", Chinese Journal of Electronics, Vol.23, No.4, pp.695-700, 2014.
    P. Joshi, S. Chaudhary and V. Kumar, Advances in Computing and Information Technology, Springer Berlin Heidelberg, Germany, pp.401-410, 2013.
    M. Cataldi and M.A. Aufaure, "The 10 million follower fallacy: Audience size does not prove domain-influence on Twitter", Knowledge & Information Systems, Vol.44, No.3, pp.559- 580, 2015.
    T. Anwar and M. Abulaish, "Ranking radically influential web forum users", IEEE Transactions on Information Forensics & Security, Vol.10, No.6, pp.1289-1298, 2015.
    M.Y. Cha, H. Haddadi and F. Benevenuto, "Measuring user influence in twitter: The million follower fallacy", Proc. of the Fourth International AAAI Conference on Weblogs and Social Media, Washington, D.C, USA, pp.10-18, 2010.
    M. Kitsak, L.K. Gallos and S. Havlin, "Identification of influential spreaders in complex networks", Nature Physics, Vol.6, No.1, pp.888-893, 2010.
    P. Brown and J.L. Feng, "Measuring user influence on twitter using modified K-shell Decomposition", Proc. of The International AAAI Conference on Weblogs and Social Media Workshop on the Social Mobile Web, Barcelona, Spain, pp.18-23, 2011.
    Y. Zhai, L. Li, X. Lin X, et al., "Evaluating user influence based on Web2.0 UGC", Proc. of 4th International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace & Electronic Systems, Aalborg, Denmark, pp.206-211, 2014.
    Y.L. Huang and L. Li, "Analysis of user influence in social network based on behavior and relationship", Proc. of the 2nd International Conference on Measurement, Information and Control, Harbin, China, pp.682-686, 2013.
    C.J. Xiao, Y.H. Zhang and X. Zeng, "Predicting user influence in social media", Journal of Networks, Vol.8, No.11, pp.2649- 2655, 2013. A Study on Influential User Identification in Online Social Networks 473
    S. Maiti, D.P. Mandal and P. Mitra, "Detecting influential users using spread of communications", 2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS), Trivandrum, India, pp.288-292, 2013.
    I. Uysal and W.B. Croft, "User oriented tweet ranking: A filtering approach to microblogs", Proc. of the 20th ACM international conference on Information and knowledge management, Glasgow, Scotland, pp.2261-2264, 2011.
    W.Z. Zhang, B.L. Wang, H. He, et al., "Public opinion leader community mining based on the heterogeneous network", Acta Electronica Sinica, Vol.40, No.10, pp.1927-1932, 2012. (in Chinese)
    X. Li, S.Y. Cheng and W.L. Chen, "Novel user influence measurement based on user interaction in microblog", IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Niagara Falls, Canada, pp.615-619, 2013.
    X.Y. Liu, H. Shen and F.L. Ma, "Topical influential user analysis with relationship strength estimation in twitter", 2014 IEEE International Conference on Data Mining Workshop (ICDMW), Shenzhen, China, pp.1012-1019, 2014.
    F. Hao, M. Chen, C. Zhu, et al., "Discovering influential users in micro-blog marketing with influence maximization mechanism", 2012 IEEE Global Communications Conference, Anaheim, USA, pp.470-474, 2012.
    J. Ren, Z.Y. Chen, J.L. Shen, et al., "Influences of influential Users: An empirical study of music social network", Proc. of International Conference on Internet Multimedia Computing and Service, Xiamen, China, pp.411, 2014.
    A. Mislove, M. Marcon, K.P. Gummadi, et al., "Measurement and Analysis of Online Social Networks", Proc. of ACM Sigcomm Conference on Internet Measurement, San Diego, USA, pp.29-42, 2007.
    J. Weng, E.P. Lim, J. Jiang, et al., "TwitterRank: Finding topic-sensitive influential twitterers", Proc. of Third ACM International Conference on Web search and data mining, New York City, USA, pp.261-270, 2010.
    L. Lv, Y.C. Zhang and C.H. Yeung, "Leaders in social networks, the delicious case", PLoS One, Vol.6, No.6, e21202, 2011.
  • 加载中


    通讯作者: 陈斌,
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (165) PDF downloads(1346) Cited by()
    Proportional views


    DownLoad:  Full-Size Img  PowerPoint