Advertisement

Tweet Stream Summarization for Online Reputation Management

  • Jorge Carrillo-de-Albornoz
  • Enrique Amigó
  • Laura Plaza
  • Julio Gonzalo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9626)

Abstract

Producing online reputation reports for an entity (company, brand, etc.) is a focused summarization task with a distinctive feature: issues that may affect the reputation of the entity take priority in the summary. In this paper we (i) propose a novel methodology to evaluate summaries in the context of online reputation which profits from an analogy between reputation reports and the problem of diversity in search; and (ii) provide empirical evidence that incorporating priority signals may benefit this summarization task.

Keywords

Summarization Diversity Tweets Reputation management 

Notes

Acknowledgments

This research was partially supported by the Spanish Ministry of Science and Innovation (VoxPopuli Project, TIN2013-47090-C3-1-P) and UNED (project 2014V/PUNED/0011).

References

  1. 1.
    Amigó, E., Carrillo-de-Albornoz, J., Chugur, I., Corujo, A., Gonzalo, J., Martín, T., Meij, E., de Rijke, M., Spina, D.: Overview of RepLab 2013: Evaluating online reputation monitoring systems. In: Forner, P., Müller, H., Paredes, R., Rosso, P., Stein, B. (eds.) CLEF 2013. LNCS, vol. 8138, pp. 333–352. Springer, Heidelberg (2013)Google Scholar
  2. 2.
    Lin, C.Y.: Rouge: A package for automatic evaluation of summaries. In: Proceedings of the ACL Workshop on Text Summarization Branches Out, pp. 74–81 (2004)Google Scholar
  3. 3.
    Moffat, A., Zobel, J.: Rank-biased precision for measurement of retrieval effectiveness. ACM Trans. Inf. Syst. (TOIS) 27(1), 2 (2008)CrossRefGoogle Scholar
  4. 4.
    Amigó, E., Gonzalo, J., Verdejo, F.: A general evaluation measure for document organization tasks. In: Proceedings of ACM SIGIR, pp. 643–652. ACM (2013)Google Scholar
  5. 5.
    Erkan, G., Radev, D.R.: Lexrank: Graph-based lexical centrality as salience in text summarization. J. Artif. Int. Res. 22(1), 457–479 (2004)Google Scholar
  6. 6.
    Radev, D., Allison, T., Blair-Goldensohn, S., Blitzer, J., Çelebi, A., Dimitrov, S., Drabek, E., Hakim, A., Lam, W., Liu, D., Otterbacher, J., Qi, H., Saggion, H., Teufel, S., Topper, M., Winkel, A., Zhang, Z.: MEAD – A platform for multidocument multilingual text summarization. In: Proceedings of LREC (2004)Google Scholar
  7. 7.
    Van Erp, M., Schomaker, L.: Variants of the borda count method for combining ranked classifier hypotheses. In: Proceedings of Seventh International Workshop on Frontiers in Handwriting recognition. pp. 443–452 (2000)Google Scholar
  8. 8.
    Cheung, J.C.K., Penn, G.: Towards robust abstractive multi-document summarization: A caseframe analysis of centrality and domain. In: Proceedings of ACL, Sofia, Bulgaria. pp. 1233–1242 (2013)Google Scholar
  9. 9.
    Mei, Q., Guo, J., Radev, D.: Divrank: The interplay of prestige and diversity in information networks. In: Proceedings of ACM SIGKDD. pp. 1009–1018 (2010)Google Scholar
  10. 10.
    Clarke, C.L., Kolla, M., Cormack, G.V., Vechtomova, O., Ashkan, A., Büttcher, S., MacKinnon, I.: Novelty and diversity in information retrieval evaluation. In: Proceedings of ACM SIGIR 2008, pp. 659–666 (2008)Google Scholar
  11. 11.
    Fiszman, M., Demner-Fushman, D., Kilicoglu, H., Rindflesch, T.C.: Automatic summarization of medline citations for evidence-based medical treatment: A topic-oriented evaluation. J. Biomed. Inform. 42(5), 801–813 (2009)CrossRefGoogle Scholar
  12. 12.
    Pang, B., Lee, L.: Opinion mining and sentiment analysis. Found. Trends Inf. Retr. 2(1–2), 1–135 (2008)CrossRefGoogle Scholar
  13. 13.
    Nastase, V.: Topic-driven multi-document summarization with encyclopedic knowledge and spreading activation. In: Proceedings of EMNLP, pp. 763–772 (2008)Google Scholar
  14. 14.
    Inouye, D., Kalita, J.: Comparing twitter summarization algorithms for multiple post summaries. In: Proceedings of the IEEE Third International Conference on Social Computing, pp. 298–306 (2011)Google Scholar
  15. 15.
    Liu, X., Li, Y., Wei, F., Zhou, M.: Graph-based multi-tweet summarization using social signals. In: Proceedings of COLING 2012, pp. 1699–1714 (2012)Google Scholar
  16. 16.
    Takamura, H., Yokono, H., Okumura, M.: Summarizing a document stream. In: Clough, P., Foley, C., Gurrin, C., Jones, G.J.F., Kraaij, W., Lee, H., Mudoch, V. (eds.) ECIR 2011. LNCS, vol. 6611, pp. 177–188. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  17. 17.
    Duan, Y., Chen, Z., Wei, F., Zhou, M., Shum, H.Y.: Twitter topic summarization by ranking tweets using social influence and content quality. In: Proceedings of COLING 2012, Mumbai, India, pp. 763–780 (2012)Google Scholar
  18. 18.
    Mihalcea, R., Tarau, P.: Textrank: Bringing order into texts. In: Proceedings of EMNLP 2004, Barcelona, Spain pp. 404–411 (2004)Google Scholar
  19. 19.
    Sharifi, B., Hutton, M.A., Kalita, J.: Summarizing microblogs automatically. In: Proceedings of NAACL, pp. 685–688 (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jorge Carrillo-de-Albornoz
    • 1
  • Enrique Amigó
    • 1
  • Laura Plaza
    • 1
  • Julio Gonzalo
    • 1
  1. 1.NLP & IR GroupUniversidad Nacional de Educación a Distancia (UNED)MadridSpain

Personalised recommendations