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Supporting Experts to Handle Tweet Collections About Significant Events

  • Ali Hürriyetoǧlu
  • Nelleke Oostdijk
  • Mustafa Erkan Başar
  • Antal van den Bosch
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10260)

Abstract

We introduce Relevancer that processes a tweet set and enables generating an automatic classifier from it. Relevancer satisfies information needs of experts during significant events. Enabling experts to combine automatic procedures with expertise is the main contribution of our approach and the added value of the tool. Even a small amount of feedback enables the tool to distinguish between relevant and irrelevant information effectively. Thus, Relevancer facilitates the quick understanding of and proper reaction to events presented on Twitter.

Keywords

Social media Text mining Machine learning Twitter 

Notes

Acknowledgments

COMMIT, Statistics Netherlands, and Floodtags supported our work.

References

  1. 1.
    Hürriyetoǧlu, A., Gudehus, C., Oostdijk, N., Bosch, A.: Relevancer: finding and labeling relevant information in tweet collections. In: Spiro, E., Ahn, Y.-Y. (eds.) SocInfo 2016. LNCS, vol. 10047, pp. 210–224. Springer, Cham (2016). doi: 10.1007/978-3-319-47874-6_15 CrossRefGoogle Scholar
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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Ali Hürriyetoǧlu
    • 1
  • Nelleke Oostdijk
    • 2
  • Mustafa Erkan Başar
    • 2
  • Antal van den Bosch
    • 2
    • 3
  1. 1.Statistics NetherlandsCZ HeerlenThe Netherlands
  2. 2.Centre for Language Studies, Radboud UniversityNijmegenThe Netherlands
  3. 3.Meertens InstituteAmsterdamThe Netherlands

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