A Graph-Based Reliable User Classification

  • Bayar Tsolmon
  • Kyung-Soon LeeEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 285)


When some hot social issue or event occurs, it will significantly increase the number of comments and retweet on that day on Twitter. However, as the amount of SNS data increases, the noise also increases synchronously, thus a reliable user classification method is being required. In this paper, we classify the users who are interested in the issue as “socially well-known user” and “reliable and highly active user”. “A graph-based user reliability measurement” and “Weekly user activity measurement” are introduced to classify users who are interested in the issue. Eight of social issues were experimented in Twitter data to verify validity of the proposed method. The top 10 results of the experiment showed 76.8 % of performance in average precision (P@10). The experimental results show that the proposed method is effective for classifying users in Twitter corpus.


Graph-based user metric User classification Timeline analysis 


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This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012R1A1A2044811).


  1. 1.
    Yang, Z., Guo, J., Cai, K., Tang, J., Li, J., Zhang, L., Su, Z.: Understanding retweeting behaviors in social networks. In Proceedings of the 19th ACM international conference on Information and knowledge management, pp. 1633-1636, ACM (2010)Google Scholar
  2. 2.
    Boyd, D., Golder, S., & Lotan, G.: Tweet, tweet, retweet: Conversational aspects of retweeting on Twitter. In System Sciences (HICSS), pp. 1-10. IEEE (2010)Google Scholar
  3. 3.
    Mendoza, M., Poblete, B., Castillo, C.: Twitter Under Crisis: Can we trust what we RT?. In Proceedings of the first workshop on social media analytics, pp. 71-79, ACM (2010).Google Scholar
  4. 4.
    Tinati, R., Carr, L., Hall, W., Bentwood, J.: Identifying communicator roles in Twitter. In Proceedings of the 21st international conference companion on World Wide Web, pp. 1161-1168, ACM (2012)Google Scholar
  5. 5.
    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
  6. 6.
    Kleinberg J. M.: Authoritative Sources in a Hyperlinked Environment, Journal of the ACM, 46(5) pp. 604-632, (1999)Google Scholar

Copyright information

© Springer Science+Business Media Singapore 2014

Authors and Affiliations

  1. 1.Division of Computer Science and Engineering, CAIITChonbuk National UniversityDeokjin-gu, Jeonju-siRepublic of Korea

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