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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Li, Q., Zhou, T., Lü, L., Chen, D.: Identifying influential spreaders by weighted LeaderRank. Phys. A Stat. Mech. Appl. 404, 47–55 (2014)
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)
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)
Zhou, T., Fu, Z.-Q., Wang, B.-H.: Epidemic dynamics on complex networks. Prog. Nat. Sci. 16(5), 452–457 (2006)
Lü, L., Zhou, T.: Link prediction in complex networks: a survey. Phys. A Stat. Mech. Appl. 390, 1150–1170 (2011)
Lu, L., Chen, D.-B., Zhou, T.: The small world yields the most effective information spreading. New J. Phys. 13, 123005 (2011)
Doerr, B., Fouz, M., Friedrich, T.: Why rumors spread so quickly in social networks. Commun. ACM 55, 70–75 (2012)
Aral, S., Walker, D.: Identifying influential and susceptible members of social networks. Science 337, 337–341 (2012)
Silva, R., Viana, M., Costa, F.: Predicting epidemic outbreak from individual features of the spreaders. J. Stat. Mech. Theor. Exp. 2012, P07005 (2012)
Lu, L., Zhang, Y.-C., Yeung, C.H., Zhou, T.: Leaders in social networks, the delicious case. PLoS One 6, e21202 (2011)
Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. Comput. Netw. ISDN Syst. 30, 107–117 (1998)
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)
Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: bringing order to the web. In: WWW 1998, pp. 161–172 (1998)
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)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Le, V.V., Nguyen, H.T., Snasel, V., Dao, T.T. (2016). Identify Influential Spreaders in Online Social Networks Based on Social Meta Path and PageRank. In: Nguyen, H., Snasel, V. (eds) Computational Social Networks. CSoNet 2016. Lecture Notes in Computer Science(), vol 9795. Springer, Cham. https://doi.org/10.1007/978-3-319-42345-6_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-42345-6_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-42344-9
Online ISBN: 978-3-319-42345-6
eBook Packages: Computer ScienceComputer Science (R0)