Advertisement

Finding Expert Role in Social-Support Online Community

  • Isma Hamid
  • Yu Wu
  • Qamar Nawaz
  • Muhammad Rauf
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 463)

Abstract

Understanding experts’ roles and behaviors in social networking sites are helpful in designing and implementation of social network systems. Social element of an expert’s role is an important aspect to be investigated that has been overlooked until recently. In this paper, to investigates the social element of experts in social support online community, we proposed a graph based feature selection approach to identify current experts in online communities. The experimental results show the effectiveness of the proposed technique in evaluating user’s expertise in online communities. The proposed technique is simple to implement in comparison to computationally expensive algorithms.

Keywords

Online communities Expert role World Wide Web 

Notes

Acknowledgments

This work was supported in part by projects including the Scientific and Technological Research Program of Chongqing Municipal Education Commission Grant (KJ13051), the Natural Science Foundation of Chongqing, China (cstc2014jcyjA40049), and the Scientific and Technological Research Program of Chongqing Municipal Education Commission (KJ130527).

References

  1. 1.
    Rowe, M., Fernandez, M., Angeletou, S., Alani, H.: Community analysis through semantic rules and role composition derivation. Web Semant. Sci. Serv. Agents World Wide Web 18, 31–47 (2013)Google Scholar
  2. 2.
    Wilson, C., Boe, B., Sala, A., Puttaswamy, K.P., Zhao, B.Y.: User interactions in social networks and their implications. In: Proceedings of the 4th ACM European Conference on Computer Systems, pp. 205–218. ACM (2009)Google Scholar
  3. 3.
    Davoodi, E., Kianmehr, K., Afsharchi, M.: A semantic social network-based expert recommender system. Appl. Intell. 39, 1–13 (2013)Google Scholar
  4. 4.
    Hautz, J., Hutter, K., Füller, J., Matzler, K., Rieger, M.: How to establish an online innovation community? The role of users and their innovative content. In: 43rd Hawaii International Conference on System Sciences, HICSS 2010, pp. 1–11. IEEE (2010)Google Scholar
  5. 5.
    Buntain, C., Golbeck, J.: Identifying social roles in reddit using network structure. In: Proceedings of the Companion Publication of the 23rd International Conference on World Wide Web Companion, pp. 615–620. International World Wide Web Conferences Steering Committee (2014)Google Scholar
  6. 6.
    Littlepage, G.E., Mueller, A.L.: Recognition and utilization of expertise in problem-solving groups: expert characteristics and behavior. Group Dyn. Theory Res. Pract. 1, 324 (1997)Google Scholar
  7. 7.
    Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank citation ranking: bringing order to the Web (1999)Google Scholar
  8. 8.
    Kleinberg, J.M.: Authoritative sources in a hyperlinked environment. J. ACM 46, 604–632 (1999)Google Scholar
  9. 9.
    Lempel, R., Moran, S.: SALSA: the stochastic approach for link-structure analysis. ACM Trans. Inf. Syst. TOIS 19, 131–160 (2001)Google Scholar
  10. 10.
    Liu, X., Bollen, J., Nelson, M.L., Van de Sompel, H.: Co-authorship networks in the digital library research community. Inf. Process. Manag. 41, 1462–1480 (2005)Google Scholar
  11. 11.
    Zhang, J., Ackerman, M.S., Adamic, L.: Expertise networks in online communities: structure and algorithms. In: Proceedings of the 16th International Conference on World Wide Web, pp. 221–230. ACM (2007)Google Scholar
  12. 12.
    Weng, J., Lim, E.-P., Jiang, J., He, Q.: Twitterrank: finding topic-sensitive influential Twitterers. In: Proceedings of the Third ACM International Conference on Web Search Data Mining, pp. 261–270. ACM (2010)Google Scholar
  13. 13.
    Bouguessa, M., Dumoulin, B., Wang, S.: Identifying authoritative actors in question-answering forums: the case of Yahoo! answers. In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 866–874. ACM (2008)Google Scholar
  14. 14.
    Pal, A., Harper, F.M., Konstan, J.A.: Exploring question selection bias to identify experts and potential experts in community question answering. ACM Trans. Inf. Syst. TOIS 30, 10 (2012)Google Scholar
  15. 15.
    Wang, G.A., Jiao, J., Abrahams, A.S., Fan, W., Zhang, Z.: ExpertRank: a topic-aware expert finding algorithm for online knowledge communities. Decis. Support Syst. 54, 1442–1451 (2013)Google Scholar
  16. 16.
    WebMD - Better information. Better health. In: WebMD. http://www.webmd.com/default.htm. Accessed 5 May 2016
  17. 17.
    Welser, H.T., Cosley, D., Kossinets, G., Lin, A., Dokshin, F., Gay, G., Smith, M.: Finding social roles in Wikipedia. In: Proceedings of the 2011 iConference, pp. 122–129. ACM (2011)Google Scholar
  18. 18.
    Welser, H.T., Gleave, E., Fisher, D., Smith, M.: Visualizing the signatures of social roles in online discussion groups. J. Soc. Struct. 8, 1–32 (2007)Google Scholar
  19. 19.
    Fisher, D.: Using egocentric networks to understand communication. Internet Comput. IEEE 9, 20–28 (2005)Google Scholar
  20. 20.
    Breiman, L.: Bagging predictors. Mach. Learn. 24, 123–140 (1996)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.College of Computer Science and TechnologyChongqing University of Posts and TelecommunicationsChongqingChina
  2. 2.Institute of AutomationUniversity of Chinese Academy of ScienceBeijingChina

Personalised recommendations