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.
This work was supported by the project GRAISearch (FP7-PEOPLE-2013-IAPP).
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Houdyer, P., Zimmerman, A., Kaytoue, M., Plantevit, M., Mitchell, J., Robardet, C. (2015). Gazouille: Detecting and Illustrating Local Events from Geolocalized Social Media Streams. In: Bifet, A., et al. Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2015. Lecture Notes in Computer Science(), vol 9286. Springer, Cham. https://doi.org/10.1007/978-3-319-23461-8_29
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DOI: https://doi.org/10.1007/978-3-319-23461-8_29
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