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Gazouille: Detecting and Illustrating Local Events from Geolocalized Social Media Streams

  • Pierre Houdyer
  • Albrecht Zimmerman
  • Mehdi KaytoueEmail author
  • Marc Plantevit
  • Joseph Mitchell
  • Céline Robardet
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9286)

Abstract

We present Gazouille, a system for discovering local events in geo-localized social media streams. The system is based on three core modules: (i) social networks data acquisition on several urban areas, (ii) event detection through time series analysis, and (iii) a Web user interface to present events discovered in real-time in a city, associated to a gallery of social media that characterize the event.

Keywords

Event Detection Discrete Fourier Transform Brand Perception Event Detection Module Newsworthy Event 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    Xia, C., Schwartz, R., Xie, K.E., Krebs, A., Langdon, A., Ting, J., Naaman, M.: Citybeat: real-time social media visualization of hyper-local city data. In: WWW 2014, Companion Volume, pp. 167–170. ACM (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Pierre Houdyer
    • 1
  • Albrecht Zimmerman
    • 2
  • Mehdi Kaytoue
    • 2
    Email author
  • Marc Plantevit
    • 3
  • Joseph Mitchell
    • 1
  • Céline Robardet
    • 2
  1. 1.Tapastreet Ltd.DublinIreland
  2. 2.INSA-Lyon, CNRS, LIRIS UMR5205LyonFrance
  3. 3.Université Lyon 1, CNRS, LIRIS UMR5205LyonFrance

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