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

Houdyer Pierre 1 Albrecht Zimmermann 2 Mehdi Kaytoue 2 Marc Plantevit 2 Joseph Mitchell 1 Céline Robardet 2
2 DM2L - Data Mining and Machine Learning
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
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.
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-01193030
Contributor : Marc Plantevit <>
Submitted on : Friday, September 4, 2015 - 10:49:49 AM
Last modification on : Thursday, November 21, 2019 - 2:27:23 AM

Identifiers

Citation

Houdyer Pierre, Albrecht Zimmermann, Mehdi Kaytoue, Marc Plantevit, Joseph Mitchell, et al.. Gazouille: Detecting and Illustrating Local Events from Geolocalized Social Media Streams. European Conference on Machine Learning and Knowledge Discovery in Databases, 2015, Porto, Portugal. pp.276-280, ⟨10.1007/978-3-319-23461-8_29⟩. ⟨hal-01193030⟩

Share

Metrics

Record views

223