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Why Do I Retweet It? An Information Propagation Model for Microblogs

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8238))

Abstract

Microblogging platforms are Web 2.0 services that represent a suitable environment for studying how information is propagated in social networks and how users can become influential. In this work we analyse the impact of the network features and of the users’ behaviour on the information diffusion. Our analysis highlights a strong relation between the level of visibility of a message in the flow of information seen by a user and the probability that the user further disseminates the message. In addition, we also highlight the existence of other latent factors that impact on the dissemination probability, correlated with the properties of the user that generated the message. Considering these results we define an information propagation model that generates information cascades (i.e. flows of messages propagated from user to user) whose statistical properties match empirical observations.

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References

  1. Galuba, W., Aberer, K., Chakraborty, D., Despotovic, Z., Kellerer, W.: Outtweeting the twitterers-predicting information cascades in microblogs. In: Proceedings of the 3rd Conference on Online Social Networks, pp. 3. USENIX Association (2010)

    Google Scholar 

  2. Bakshy, E., Hofman, J.M., Mason, W.A., Watts, D.J.: Everyone’s an influencer: quantifying influence on twitter. In: Proceedings of the fourth ACM International Conference on Web Search and Data Mining, pp. 65–74. ACM (2011)

    Google Scholar 

  3. Ye, S., Wu, S.F.: Measuring message propagation and social influence on twitter.com. In: Bolc, L., Makowski, M., Wierzbicki, A. (eds.) SocInfo 2010. LNCS, vol. 6430, pp. 216–231. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  4. Sun, E., Rosenn, I., Marlow, C., Lento, T.M.: Gesundheit! modeling contagion through facebook news feed. In: ICWSM (2009)

    Google Scholar 

  5. Cha, M., Mislove, A., Adams, B., Gummadi, K.P.: Characterizing social cascades in flickr. In: Proceedings of the First Workshop on Online Social Networks, pp. 13–18. ACM (2008)

    Google Scholar 

  6. Leskovec, J., McGlohon, M., Faloutsos, C., Glance, N., Hurst, M.: Cascading behavior in large blog graphs. arXiv preprint arXiv:0704.2803 (2007)

    Google Scholar 

  7. Szabo, G., Huberman, B.A.: Predicting the popularity of online content. Communications of the ACM 53, 80–88 (2010)

    Article  Google Scholar 

  8. Susarla, A., Oh, J.H., Tan, Y.: Social networks and the diffusion of user-generated content: Evidence from youtube. Information Systems Research 23, 23–41 (2012)

    Article  Google Scholar 

  9. Oken Hodas, N., Lerman, K.: How visibility and divided attention constrain social contagion (2012)

    Google Scholar 

  10. Kwak, H., Lee, C., Park, H., Moon, S.: What is twitter, a social network or a news media? In: Proceedings of the 19th International Conference on World Wide Web, pp. 591–600. ACM (2010)

    Google Scholar 

  11. Arnaboldi, V., Conti, M., Passarella, A., Pezzoni, F.: Ego networks in twitter: an experimental analysis. In: The Fifth IEEE International Workshop on Network Science for Communication Networks, NetSciCom 2013 (2013)

    Google Scholar 

  12. Cha, M., Haddadi, H., Benevenuto, F., Gummadi, P.K.: Measuring user influence in twitter: The million follower fallacy. In: ICWSM, vol. 10, pp. 10–17 (2010)

    Google Scholar 

  13. Suh, B., Hong, L., Pirolli, P., Chi, E.H.: Want to be retweeted? large scale analytics on factors impacting retweet in twitter network. In: 2010 IEEE Second International Conference on Social Computing (SocialCom), pp. 177–184. IEEE (2010)

    Google Scholar 

  14. Newman, M.E.: The structure and function of complex networks. SIAM Review 45, 167–256 (2003)

    Article  MathSciNet  MATH  Google Scholar 

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© 2013 Springer International Publishing Switzerland

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Pezzoni, F., An, J., Passarella, A., Crowcroft, J., Conti, M. (2013). Why Do I Retweet It? An Information Propagation Model for Microblogs. In: Jatowt, A., et al. Social Informatics. SocInfo 2013. Lecture Notes in Computer Science, vol 8238. Springer, Cham. https://doi.org/10.1007/978-3-319-03260-3_31

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  • DOI: https://doi.org/10.1007/978-3-319-03260-3_31

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03259-7

  • Online ISBN: 978-3-319-03260-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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