Exploring Interactions in Social Networks for Influence Discovery

  • Monika Ewa RakoczyEmail author
  • Amel Bouzeghoub
  • Katarzyna Wegrzyn-Wolska
  • Alda Lopes Gancarski
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 354)


Today’s social networks allow users to react to new contents such as images, posts and messages in numerous ways. For example, a user, impressed by another user’s post, might react to it by liking it and then sharing it forward to her friends. Therefore, a successful estimation of the influence between users requires models to be expressive enough to fully describe various reactions. In this article, we aim to utilize those direct reactive activities, in order to calculate users impact on others. Hence, we propose a flexible method that considers type, quality, quantity and time of reactions and, as a result, the method assesses the influence dependencies within the social network. The experiments conducted using two different real-world datasets of Facebook and Pinterest show the adequacy and flexibility of the proposed model that is adaptive to data having different features.


Influence Influencers Social scoring Social network analysis 


  1. 1.
    The psychology of sharing. why do people share online? The New York Times Customer Insight Group (2011). Accessed 18 May 2018
  2. 2.
    Burke, M., Kraut, R.E.: Growing closer on facebook: changes in tie strength through social network site use. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 4187–4196. ACM (2014)Google Scholar
  3. 3.
    Chen, W., Lin, T., Tan, Z., Zhao, M., Zhou, X.: Robust influence maximization. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 795–804. ACM (2016)Google Scholar
  4. 4.
    Kempe, D., Kleinberg, J.M., Tardos, É.: Maximizing the spread of influence through a social network. Theory Comput. 11, 105–147 (2015)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Kitsak, M., et al.: Identification of influential spreaders in complex networks. arXiv preprint arXiv:1001.5285 (2010)CrossRefGoogle Scholar
  6. 6.
    Laflin, P., Mantzaris, A.V., Ainley, F., Otley, A., Grindrod, P., Higham, D.J.: Discovering and validating influence in a dynamic online social network. Soc. Netw. Anal. Min. 3(4), 1311–1323 (2013)CrossRefGoogle Scholar
  7. 7.
    Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: bringing order to the web. Technical report, Stanford InfoLab (1999)Google Scholar
  8. 8.
    Rames, A., Rodriguez, M., Getoor, L.: Multi-relational influence models for online professional networks. In: Proceedings of the International Conference on Web Intelligence, pp. 291–298. ACM (2017)Google Scholar
  9. 9.
    Rao, A., Spasojevic, N., Li, Z., DSouza, T.: Klout score: measuring influence across multiple social networks. In: 2015 IEEE International Conference on Big Data (Big Data), pp. 2282–2289. IEEE (2015)Google Scholar
  10. 10.
    Scissors, L., Burke, M., Wengrovitz, S.: What’s in a like?: attitudes and behaviors around receiving likes on facebook. In: Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, pp. 1501–1510. ACM (2016)Google Scholar
  11. 11.
    Spasojevic, N., Li, Z., Rao, A., Bhattacharyya, P.: When-to-post on social networks. In: Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 2127–2136. ACM (2015)Google Scholar
  12. 12.
    Zafarani, R., Abbasi, M.A., Liu, H.: Social Media Mining: An Introduction. Cambridge University Press, New York (2014)CrossRefGoogle Scholar
  13. 13.
    Zhong, C., Shah, S., Sundaravadivelan, K., Sastry, N.: Sharing the loves: understanding the how and why of online content curation. In: 7th International AAAI Conference on Weblogs and Social Media (ICWSM13), Boston, US, July 2013Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Monika Ewa Rakoczy
    • 1
    Email author
  • Amel Bouzeghoub
    • 1
  • Katarzyna Wegrzyn-Wolska
    • 2
  • Alda Lopes Gancarski
    • 1
  1. 1.SAMOVAR, CNRS, Telecom SudParisEvryFrance
  2. 2.Efrei ParisVillejuifFrance

Personalised recommendations