Detecting Rumors Through Modeling Information Propagation Networks in a Social Media Environment
详细信息    查看全文
  • 关键词:Rumor detection ; Heterogeneous user representation and modeling ; Information propagation model ; Information credibility in social media
  • 刊名:Lecture Notes in Computer Science
  • 出版年:2015
  • 出版时间:2015
  • 年:2015
  • 卷:9021
  • 期:1
  • 页码:121-130
  • 全文大小:164 KB
  • 参考文献:1. Yang, F., Liu, Y., Yu, X., Yang, M.: Automatic detection of rumor on sina weibo. In: Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics, pp. 13:1a€-3:7. ACM (2012)
    2. Castillo, C., Mendoza, M., Poblete, B.: Information credibility on twitter. In: Proceedings of the 20th International Conference on World Wide Web, pp. 675a€-84. ACM (2011)
    3. Qazvinian, V., Rosengren, E., Radev, D.R., Mei, Q.Z.: Rumor has it: Identifying misinformation in microblogs. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 1589a€-599. Association for Computational Linguistics (2011)
    4. Moreno, Y, Nekovee, M, Pacheco, AF (2004) Dynamics of rumor spreading in complex networks. Physical Review E 69: pp. 066130 CrossRef
    5. Xia, Z., Huang, L.L.: Emergence of social rumor: Modeling, analysis, and simulations. In: Proceedings of the 7th International Conference on Computational Science, pp. 90a€-7. Springer (2007)
    6. Suh, B., Hong, L., Pirolli, P., Chi, E.H.: Want to be retweeted? large scale analytics on factors impacting retweet in twitter network. In: Proceedings of the 2010 IEEE Second International Conference on Social Computing (SocialCom), pp. 177a€-84. IEEE (2010)
    7. Jin, F., Dougherty, E., Saraf, P., Cao, Y., Ramakrishnan, N: Epidemiological modeling of news and rumors on twitter. In: Proceedings of the 7th Workshop on Social Network Mining and Analysis, pp. 8:1a€-:9. ACM (2013)
    8. Sun, S, Liu, H, He, J, Du, X Detecting event rumors on sina weibo automatically. In: Ishikawa, Y, Li, J, Wang, W, Zhang, R, Zhang, W eds. (2013) Web Technologies and Applications. Springer, Heidelberg, pp. 120-131 CrossRef
    9. Liao, Q.Y., Shi, L.: She gets a sports car from our donation: rumor transmission in a chinese microblogging community. In: Proceedings of the 2013 Conference on Computer Supported Cooperative Work, pp. 587a€-98. ACM (2013)
    10. Lei, K., Zhang, K., Xu, K.: Understanding sina weibo online social network: A community approach. In: Proceedings of the 2013 IEEE Global Communications Conference (GLOBECOM), pp. 3114a€-119. IEEE (2013)
    11. Cai, G., Wu, H., Lv, R.: Rumors detection in chinese via crowd responses. In: Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 912a€-17 (2014)
    12. Bao, Y.Y., Yi, C.Q., Xue, Y.B., Dong, Y.F.: A new rumor propagation model and control strategy on social networks. In: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 1472a€-473 (2013)
    13. Liu, D.C., Chen, X.: Rumor propagation in online social networks like twitter-a simulation study. In: Proceedings of the Third International Conference on Multimedia Information Networking and Security (MINES), pp. 278a€-82. IEEE (2011)
    14. Weibo Rumor Busting. http://weibo.com/weibopiyao
    15. Weibo Hot Topics. http://d.weibo.com
  • 作者单位:Social Computing, Behavioral-Cultural Modeling, and Prediction
  • 丛书名:978-3-319-16267-6
  • 刊物类别:Computer Science
  • 刊物主题:Artificial Intelligence and Robotics
    Computer Communication Networks
    Software Engineering
    Data Encryption
    Database Management
    Computation by Abstract Devices
    Algorithm Analysis and Problem Complexity
  • 出版者:Springer Berlin / Heidelberg
  • ISSN:1611-3349
文摘
In the midst of todaya€?s pervasive influence of social media content and activities, information credibility has increasingly become a major issue. Accordingly, identifying false information, e.g. rumors circulated in social media environments, attracts expanding research attention and growing interests. Many previous studies have exploited user-independent features for rumor detection. These prior investigations uniformly treat all users relevant to the propagation of a social media message as instances of a generic entity. Such a modeling approach usually adopts a homogeneous network to represent all users, the practice of which ignores the variety across an entire user population in a social media environment. Recognizing this limitation of modeling methodologies, this study explores user-specific features in a social media environment for rumor detection. The new approach hypothesizes that whether a user tends to spread a rumor is dependent upon specific attributes of the user in addition to content characteristics of the message itself. Under this hypothesis, information propagation patterns of rumors versus those of credible messages in a social media environment are systematically differentiable. To explore and exploit this hypothesis, we develop a new information propagation model based on a heterogeneous user representation for rumor recognition. The new approach is capable of differentiating rumors from credible messages through observing distinctions in their respective propagation patterns in social media. Experimental results show that the new information propagation model based on heterogeneous user representation can effectively distinguish rumors from credible social media content.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700