Combining Agent-Based and Social Network Analysis Approaches to Recognition of Role Influence in Social Media

  • Bogdan Gliwa
  • Jarosław KoźlakEmail author
  • Anna Zygmunt
  • Yves Demazeau
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9662)


These days, different forms of social media play a significant role in the functioning of individuals and society, and social network analysis methodology ensures a better understanding of the structure and behaviour of societies forming in such environments. Including an agent–based approach to such analyses allows a more complete understanding of the specificity of given users as well as the local interactions between them. In this paper we introduce a multi–agent model of user organisations in social media, and analyse roles in social organisations based on distinguishing features of user behaviour such as activity, cooperativeness and group formation. We also analyse the range of influence of users playing given roles in the society, taking into consideration the consequences of removal of users with specific roles and carry out several experiments with data from the political blogosphere.


Social multi–agent system organisation Social network analysis (SNA) Social group detection Group dynamics 


  1. 1.
    Costa, A., Demazeau, Y.: Towards a formal model of multi-agent systems with dynamic organizations. In: Proceedings of the International Conference on Multi-Agent Systems, Kyoto, Japan. MIT Press publisher, Cambridge (1996)Google Scholar
  2. 2.
    Davidsson, P.: Multi agent based simulation: beyond social simulation. In: Moss, S., Davidsson, P. (eds.) MABS 2000. LNCS (LNAI), vol. 1979, pp. 97–107. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  3. 3.
    Demazeau, Y., Costa, A.R.: Populations and organizations in open multi-agent systems. In: 1st National Symposium on Parallel and Distributed AI (PDAI 1996) (1996)Google Scholar
  4. 4.
    Eyal, R., Rosenfeld, A., Sina, S., Kraus, S.: Predicting and identifying missing node information in social networks. ACM Trans. Knowl. Discov. Data 8(3), 14:1–14:35 (2013)CrossRefGoogle Scholar
  5. 5.
    Fox, M.: An organizational view of distributed systems. IEEE Trans. Syst. Man Cybern. 11(1), 70–80 (1981)CrossRefGoogle Scholar
  6. 6.
    Franchi, E., Poggi, A.: Multi-agent systems and social networks. In: Business Social Networking: Organizational, Managerial, and Technological Dimensions. IGI Global (2011)Google Scholar
  7. 7.
    Gliwa, B., Koźlak, J., Zygmunt, A., Cetnarowicz, K.: Models of social groups in blogosphere based on information about comment addressees and sentiments. In: Aberer, K., Flache, A., Jager, W., Liu, L., Tang, J., Guéret, C. (eds.) SocInfo 2012. LNCS, vol. 7710, pp. 475–488. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  8. 8.
    Gliwa, B., Saganowski, S., Zygmunt, A., Bródka, P., Kazienko, P., Koźlak, J.: Identification of group changes in blogosphere. In: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012, Istanbul, Turkey, 26–29 August 2012. IEEE Computer Society (2012)Google Scholar
  9. 9.
    Gliwa, B., Zygmunt, A., Koźlak, J.: Analysis of roles and groups in blogosphere. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds.) CORES 2013. AISC, vol. 226, pp. 303–312. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  10. 10.
    Horling, B., Lesser, V.: A survey of multi-agent organizational paradigms. Knowl. Eng. Rev. 19(4), 281–316 (2004)CrossRefGoogle Scholar
  11. 11.
    Jaccard, P.: The distribution of the flora in the alpine zone.1. New Phytol. 11(2), 37–50 (1912)CrossRefGoogle Scholar
  12. 12.
    Lacomme, L., Camps, V., Demazeau, Y., Hautefeuille, F., Jouve, B.: Middle age social networks: a dynamic organizational study. In: Demazeau, Y., Pěchoucěk, M., Corchado, J., Pěrez, J. (eds.) Advances on Practical Applications of Agents and Multiagent Systems. Advances in Intelligent and Soft Computing, pp. 211–216. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  13. 13.
    Lamarche-Perrin, R., Demazeau, Y., Vincent, J.-M.: How to build the best macroscopic description of your multi-agent system? In: Demazeau, Y., Ishida, T., Corchado, J.M., Bajo, J. (eds.) PAAMS 2013. LNCS, vol. 7879, pp. 157–169. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  14. 14.
    Leskovec, J., Huttenlocher, D., Kleinberg, J.: Predicting positive and negative links in online social networks. In: Proceedings of the 19th International Conference on World Wide Web, WWW 2010, pp. 641–650. ACM, New York (2010)Google Scholar
  15. 15.
    Palla, G., Derényi, I., Farkas, I., Vicsek, T.: Uncovering the overlapping community structure of complex networks in nature and society. Nature 435(7043), 814–818 (2005)CrossRefGoogle Scholar
  16. 16.
    Saganowski, S., Gliwa, B., Bródka, P., Zygmunt, A., Kazienko, P., Koźlak, J.: Predicting community evolution in social networks. Entropy 17(5), 3053–3096 (2015)CrossRefGoogle Scholar
  17. 17.
    Sina, S., Rosenfeld, A., Kraus, S.: Sami: an algorithm for solving the missing node problem using structure and attribute information. Soc. Netw. Analys. Min. 5(1), 54:1–54:20 (2015)Google Scholar
  18. 18.
    Tambe, M.: Towards flexible teamwork. J. Artif. Int. Res. 7(1), 83–124 (1997)Google Scholar
  19. 19.
    Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications, vol. 8. Cambridge University Press, Cambridge (1994)CrossRefzbMATHGoogle Scholar
  20. 20.
    Weerdt, M.M., Zhang, Y., Klos, T.: Multiagent task allocation in social networks. Auton. Agent. Multi-Agent Syst. 25(1), 46–86 (2011)CrossRefGoogle Scholar
  21. 21.
    Zygmunt, A.: Role identification of social networkers. In: Alhajj, R., Rokne, J. (eds.) Encyclopedia of Social Network Analysis and Mining, pp. 1598–1606. Springer, New York (2014)Google Scholar
  22. 22.
    Zygmunt, A., Bródka, P., Kazienko, P., Koźlak, J.: Key person analysis in social communities within the blogosphere. J. UCS 18(4), 577–597 (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Bogdan Gliwa
    • 1
  • Jarosław Koźlak
    • 1
    Email author
  • Anna Zygmunt
    • 1
  • Yves Demazeau
    • 2
  1. 1.AGH University of Science and TechnologyKrakówPoland
  2. 2.CNRS, Laboratoire d’Informatique de GrenobleGrenobleFrance

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