Table of Contents Author Guidelines Submit a Manuscript
Abstract and Applied Analysis
Volume 2013 (2013), Article ID 893961, 13 pages
Research Article

Hot Topic Propagation Model and Opinion Leader Identifying Model in Microblog Network

School of Information Science and Technology, Jinan University, Guangzhou 510632, China

Received 15 August 2013; Revised 30 October 2013; Accepted 3 November 2013

Academic Editor: Rafael Jacinto Villanueva

Copyright © 2013 Yan Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. DCCI Internet data center, “Chinese microblogging Blue Book,” Report statistics, 2012, (Chinese).
  2. L. Zhao, R.-X. Yuan, X.-H. Guan, and Q.-S. Jia, “Bursty propagation model for incidental events in blog networks,” Journal of Software, vol. 20, no. 5, pp. 1384–1392, 2009 (Chinese). View at Publisher · View at Google Scholar · View at Scopus
  3. B. Zhang, X. H. Guan, M. J. Khan, and Y. D. Zhou, “A time-varying propagation model of hot topic on BBS sites and Blog networks,” Information Sciences, vol. 187, no. 1, pp. 15–32, 2012. View at Publisher · View at Google Scholar · View at Scopus
  4. Q. Yan, L. Wu, C. Liu, and X. Li, “Information propagation in online social network based on human dynamics,” Abstract and Applied Analysis, vol. 2013, Article ID 953406, 6 pages, 2013. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  5. P. Chen and N. Gao, “The simulation of rumor’s spreading and controlling in micro-blog users’ network,” Journal of Software Engineering and Applications, vol. 6, pp. 102–105, 2013. View at Google Scholar
  6. S. Kazumi, R. Akano, and M. Kimura, “Prediction of information diffusion probabilities for independent cascade model,” in Knowledge-Based Intelligent Information and Engineering Systems, R. Goebel, J. Siekmann, and W. Wahlster, Eds., pp. 67–75, Springer, Berlin, Germany, 2008. View at Google Scholar
  7. M. Kimura, K. Saito, R. Nakano, and H. Motoda, “Finding influential nodes in a social network from information diffusion data,” in Social Computing and Behavioral Modeling, H. Liu, J. J. Salerno, and M. J. Young, Eds., pp. 138–145, Springer, New York, NY, USA, 2009. View at Google Scholar
  8. R. Afrasiabi and M. Benyoucef, “Measuring propagation in online social networks: the case of youtube,” Journal of Information Systems Applied Research, vol. 5, pp. 26–35, 2012. View at Google Scholar
  9. H. Yoganarasimhan, “Impact of social network structure on content propagation: a study using YouTube data,” Quantitative Marketing and Economics, vol. 10, no. 1, pp. 111–150, 2012. View at Publisher · View at Google Scholar · View at Scopus
  10. Z. Zhai, H. Xu, and P. Jia, “Identifying opinion leaders in BBS,” in Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT '08), vol. 3, pp. 398–401, December 2008. View at Publisher · View at Google Scholar · View at Scopus
  11. Z. M. Liu and L. Liu, “Recognition and analysis of opinion leaders in microblog public opinions,” Systems Engineering, vol. 29, no. 6, pp. 8–16, 2011 (Chinese). View at Google Scholar
  12. F. Li and T. C. Du, “Who is talking? An ontology-based opinion leader identification framework for word-of-mouth marketing in online social blogs,” Decision Support Systems, vol. 51, no. 1, pp. 190–197, 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. Y. Li, “An improved mix framework for opinion leader identification in online learning communities,” Knowledge-Based Systems, vol. 43, pp. 43–51, 2013. View at Google Scholar
  14. S. A. Hudli, A. A. Hudli, and A. V. Hudli, “Identifying online opinion leaders using K-means clustering,” in Proceedings of 12th International Conference Intelligent Systems Design and Applications, pp. 416–419, 2012.
  15. X. D. Song, Y. Chi, K. Hino, and B. L. Tseng, “Identifying opinion leaders in the blogosphere,” in Proceedings of the 16th ACM Conference on Information and Knowledge Management (CIKM '07), pp. 971–974, November 2007. View at Publisher · View at Google Scholar · View at Scopus
  16. X. H. Fan, J. Zhao, B. X. Fang, and Y. X. Li, “Influence diffusion probability model and utilizing it to identify network opinion leader,” Chinese Journal of Computers, vol. 36, no. 2, pp. 360–367, 2013. View at Google Scholar
  17. J. Akshay, K. Pranam, F. Tim, and O. Tim, “Modeling the spread of influence on the blogosphere,” in Proceedings of the 15th International World Wide Web Conference, 2006.
  18. PageRank, Wikipedia, 2013,