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How and why exploit tweet's location information?

Flavien Bouillot 1 Pascal Poncelet 2 Mathieu Roche 3
2 TATOO - Fouille de données environnementales
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
3 TEXTE - Exploration et exploitation de données textuelles
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Tweets exchanged over the Internet represent an important source of information, even if their characteristics make them difficult to analyze (e.g. a maximum of 140 characters, etc.). In addition associated to every message, lots of information such as location or date, are available. Taking into account these meta-information can be very useful for the decision maker. Obviously, due to the characteristics of tweets, relevant information are not expressed. For instance when considering tweets about natural disasters, an automatic extraction of location can significantly improve the analysis. In this paper, we propose a new approach to automatically extract and exploit the information about location. We also propose the end-user with a geographical hierarchy in order to improve the analysis of a set of tweets. Experiments carried out on real medical data underline the relevance of our proposal.
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Contributor : Mathieu Roche <>
Submitted on : Friday, August 10, 2012 - 8:31:01 PM
Last modification on : Thursday, June 3, 2021 - 3:32:11 PM
Long-term archiving on: : Sunday, November 11, 2012 - 2:30:29 AM


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  • HAL Id : lirmm-00723570, version 1



Flavien Bouillot, Pascal Poncelet, Mathieu Roche. How and why exploit tweet's location information?. AGILE International Conference on Geographic Information Science, AGILE: Association of Geographic Information Laboratories in Europe, Apr 2012, Avignon, France. ⟨lirmm-00723570⟩



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