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Identify Influential Spreaders in Online Social Networks Based on Social Meta Path and PageRank

  • Vang V. Le
  • Hien T. Nguyen
  • Vaclav Snasel
  • Tran Trong Dao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9795)

Abstract

Identifying “influential spreader” is finding a subset of individuals in the social network, so that when information injected into this subset, it is spread most broadly to the rest of the network individuals. The determination of the information influence degree of individual plays an important role in online social networking. Once there is a list of individuals who have high influence, the marketers can access these individuals and seek them to impress, bribe or somehow make them spread up the good information for their business as well as their product in marketing campaign. In this paper, according to the idea “Information can be spread between two unconnected users in the network as long as they both check-in at the same location”, we proposed an algorithm called SMPRank (Social Meta Path Rank) to identify individuals with the largest influence in complex online social networks. The experimental results show that SMPRank performs better than Weighted LeaderRank because of the ability to determinate more influential spreaders.

Keywords

Influential spreader LeaderRank Random walk PageRank Social meta path 

References

  1. 1.
    Li, Q., Zhou, T., Lü, L., Chen, D.: Identifying influential spreaders by weighted LeaderRank. Phys. A Stat. Mech. Appl. 404, 47–55 (2014)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Zhang, T., Liang, X.: A novel method of identifying influential nodes in complex networks based on random walks. J. Inf. Comput. Sci. 11(18), 6735–6740 (2014)CrossRefGoogle Scholar
  3. 3.
    Zhan, Q., Zhang, J., Wang, S., Yu, P.S., Xie, J.: Influence maximization across partially aligned heterogenous social networks. In: Cao, T., Lim, E.-P., Zhou, Z.-H., Ho, T.-B., Cheung, D., Motoda, H. (eds.) PAKDD 2015. LNCS, vol. 9077, pp. 58–69. Springer, Heidelberg (2015)Google Scholar
  4. 4.
    Zhou, T., Fu, Z.-Q., Wang, B.-H.: Epidemic dynamics on complex networks. Prog. Nat. Sci. 16(5), 452–457 (2006)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Lü, L., Zhou, T.: Link prediction in complex networks: a survey. Phys. A Stat. Mech. Appl. 390, 1150–1170 (2011)CrossRefGoogle Scholar
  6. 6.
    Lu, L., Chen, D.-B., Zhou, T.: The small world yields the most effective information spreading. New J. Phys. 13, 123005 (2011)CrossRefGoogle Scholar
  7. 7.
    Doerr, B., Fouz, M., Friedrich, T.: Why rumors spread so quickly in social networks. Commun. ACM 55, 70–75 (2012)CrossRefGoogle Scholar
  8. 8.
    Aral, S., Walker, D.: Identifying influential and susceptible members of social networks. Science 337, 337–341 (2012)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Silva, R., Viana, M., Costa, F.: Predicting epidemic outbreak from individual features of the spreaders. J. Stat. Mech. Theor. Exp. 2012, P07005 (2012)CrossRefGoogle Scholar
  10. 10.
    Lu, L., Zhang, Y.-C., Yeung, C.H., Zhou, T.: Leaders in social networks, the delicious case. PLoS One 6, e21202 (2011)CrossRefGoogle Scholar
  11. 11.
    Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. Comput. Netw. ISDN Syst. 30, 107–117 (1998)CrossRefGoogle Scholar
  12. 12.
    Cataldi, M., Di Caro, L., Schifanella, C.: Emerging topic detection on Twitter based on temporal and social terms evaluation. In: Proceedings of the Tenth International Workshop on Multimedia Data Mining, MDMKDD 2010, pp. 4–13 (2010)Google Scholar
  13. 13.
    Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: bringing order to the web. In: WWW 1998, pp. 161–172 (1998)Google Scholar
  14. 14.
    Kempe, D., Kleinberg, J., Tardos, E.: Maximizing the spread of influence through a social network. In: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2003, pp. 137–146. ACM, New York (2003)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Vang V. Le
    • 1
  • Hien T. Nguyen
    • 1
  • Vaclav Snasel
    • 2
  • Tran Trong Dao
    • 3
  1. 1.Faculty of Information TechnologyTon Duc Thang University Ho Chi Minh CityVietnam
  2. 2.Department of Computer ScienceVSB-Technical University of OstravaOstravaCzech Republic
  3. 3.Division of MERLINTon Duc Thang University Ho Chi Minh CityVietnam

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