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An Optimization Approach for Sub-event Detection and Summarization in Twitter

  • Polykarpos MeladianosEmail author
  • Christos Xypolopoulos
  • Giannis Nikolentzos
  • Michalis Vazirgiannis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10772)

Abstract

In this paper, we present a system that generates real-time summaries of events using only posts collected from Twitter. The system both identifies important moments within the event and generates a corresponding textual description. First, the set of tweets posted in a short time interval is represented as a weighted graph-of-words. To identify important moments within an event, the system detects rapid changes in the graphs’ edge weights using a convex optimization formulation. The system then extracts a few tweets that best describe the chain of interesting occurrences in the event using a greedy algorithm that maximizes a nondecreasing submodular function. Through extensive experiments on real-world sporting events, we show that the proposed system can effectively capture the sub-events, and that it clearly outperforms the dominant sub-event detection method.

References

  1. 1.
    Akbari, M., Hu, X., Nie, L., Chua, T.S.: From tweets to wellness: wellness event detection from Twitter streams. In: AAAI, pp. 87–93 (2016)Google Scholar
  2. 2.
    Becker, H., Naaman, M., Gravano, L.: Beyond trending topics: real-world event identification on Twitter. ICWSM 11, 438–441 (2011)Google Scholar
  3. 3.
    Castillo, C.: Big Crisis Data. Cambridge University Press, Cambridge (2016)CrossRefGoogle Scholar
  4. 4.
    Chakrabarti, D., Punera, K.: Event summarization using tweets. In: ICWSM, pp. 66–73 (2011)Google Scholar
  5. 5.
    Chierichetti, F., Kleinberg, J., Kumar, R., Mahdian, M., Pandey, S.: Event detection via communication pattern analysis. In: ICWSM, pp. 51–60 (2014)Google Scholar
  6. 6.
    Java, A., Song, X., Finin, T., Tseng, B.: Why we Twitter: understanding microblogging usage and communities. In: SNA-KDD, pp. 56–65 (2007)Google Scholar
  7. 7.
    Letsios, M., Balalau, O.D., Danisch, M., Orsini, E., Sozio, M.: Finding heaviest k-subgraphs and events in social media. In: ICDM Workshops, pp. 113–120 (2016)Google Scholar
  8. 8.
    Lin, H., Bilmes, J.: A Class of submodular functions for document summarization. In: ACL, pp. 510–520 (2011)Google Scholar
  9. 9.
    Lin, J., Roegiest, A., Tan, L., McCreadie, R., Voorhees, E., Diaz, F.: Overview of the TREC 2016 real-time summarization track. In: TREC, vol. 16 (2016)Google Scholar
  10. 10.
    Mackie, S., McCreadie, R., Macdonald, C., Ounis, I.: Comparing algorithms for microblog summarisation. In: Kanoulas, E., Lupu, M., Clough, P., Sanderson, M., Hall, M., Hanbury, A., Toms, E. (eds.) CLEF 2014. LNCS, vol. 8685, pp. 153–159. Springer, Cham (2014).  https://doi.org/10.1007/978-3-319-11382-1_15 Google Scholar
  11. 11.
    Meladianos, P., Nikolentzos, G., Rousseau, F., Stavrakas, Y., Vazirgiannis, M.: Degeneracy-based real-time sub-event detection in Twitter stream. In: ICWSM, pp. 248–257 (2015)Google Scholar
  12. 12.
    Meladianos, P., Tixier, A.J.P., Nikolentzos, G., Vazirgiannis, M.: Real-time keyword extraction from conversations. In: EACL, pp. 462–467 (2017)Google Scholar
  13. 13.
    Mihalcea, R., Tarau, P.: TextRank: bringing order into texts. In: EMNLP, pp. 404–411 (2004)Google Scholar
  14. 14.
    Nemhauser, G.L., Wolsey, L.A., Fisher, M.L.: An analysis of approximations for maximizing submodular set functions I. Math. Program. 14(1), 265–294 (1978)MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Nenkova, A., McKeown, K.: A survey of text summarization techniques. In: Aggarwal, C., Zhai, C. (eds.) Mining Text Data, pp. 43–76. Springer, Boston (2012).  https://doi.org/10.1007/978-1-4614-3223-4_3 CrossRefGoogle Scholar
  16. 16.
    Nichols, J., Mahmud, J., Drews, C.: Summarizing sporting events using Twitter. In: IUI, pp. 189–198 (2012)Google Scholar
  17. 17.
    Nikolentzos, G., Meladianos, P., Rousseau, F., Stavrakas, Y., Vazirgiannis, M.: Shortest-path graph kernels for document similarity. In: EMNLP, pp. 1891–1901 (2017)Google Scholar
  18. 18.
    Petrović, S., Osborne, M., Lavrenko, V.: Streaming first story detection with application to Twitter. In: NAACL-HLT, pp. 181–189 (2010)Google Scholar
  19. 19.
    Sharifi, B., Hutton, M.A., Kalita, J.K.: Experiments in microblog summarization. In: SocialCom, pp. 49–56 (2010)Google Scholar
  20. 20.
    Shen, C., Liu, F., Weng, F., Li, T.: A participant-based approach for event summarization using Twitter streams. In: NAACL-HLT, pp. 1152–1162 (2013)Google Scholar
  21. 21.
    Srijith, P., Hepple, M., Bontcheva, K., Preotiuc-Pietro, D.: Sub-story detection in twitter with hierarchical dirichlet processes. Inf. Process. Manage. 53, 989–1003 (2016)CrossRefGoogle Scholar
  22. 22.
    Walther, M., Kaisser, M.: Geo-spatial event detection in the Twitter stream. In: Serdyukov, P., Braslavski, P., Kuznetsov, S.O., Kamps, J., Rüger, S., Agichtein, E., Segalovich, I., Yilmaz, E. (eds.) ECIR 2013. LNCS, vol. 7814, pp. 356–367. Springer, Heidelberg (2013).  https://doi.org/10.1007/978-3-642-36973-5_30 CrossRefGoogle Scholar
  23. 23.
    Weng, J., Lee, B.S.: Event detection in Twitter. In: ICWSM, pp. 401–408 (2011)Google Scholar
  24. 24.
    Zhao, S., Zhong, L., Wickramasuriya, J., Vasudevan, V.: Human as real-time sensors of social and physical events: a case study of Twitter and sports games. arXiv:1106.4300 (2011)
  25. 25.
    Zhou, X., Chen, L.: Event detection over twitter social media streams. VLDB J. 23(3), 381–400 (2014)MathSciNetCrossRefGoogle Scholar
  26. 26.
    Zubiaga, A., Spina, D., Amigó, E., Gonzalo, J.: Towards real-time summarization of scheduled events from Twitter streams. In: HT, pp. 319–320 (2012)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Polykarpos Meladianos
    • 1
    • 2
    Email author
  • Christos Xypolopoulos
    • 1
  • Giannis Nikolentzos
    • 1
    • 2
  • Michalis Vazirgiannis
    • 1
    • 2
  1. 1.Lix, École PolytechniquePalaiseauFrance
  2. 2.Athens University of Economics and BusinessAthensGreece

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