Automatic information retrieval from tweets: A semantic clustering approach

Julien Coche, Aurelie Montarnal, Andrea Tapia, Frederick Benaben

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Much has been said about the value of social media messages for emergency services. The new uses related to these platforms bring users to share information, otherwise unknown in crisis events. Thus, many studies have been performed in order to identify tweets relating to a crisis event or to classify these tweets according to certain categories. However, determining the relevant information contained in the messages collected remains the responsibility of the emergency services. In this article, we introduce the issue of classifying the information contained in the messages. To do so, we use classes such as those used by the operators in the call centers. Particularly we show that this problem is related to named entities recognition on tweets. We then explain that a semi-supervised approach might be beneficial, as the volume of data to perform this task is low. In a second part, we present some of the challenges raised by this problematic and different ways to answer it. Finally, we explore one of them and its possible outcomes.

Original languageEnglish (US)
Title of host publicationISCRAM 2020 - Proceedings
Subtitle of host publication17th International Conference on Information Systems for Crisis Response and Management
EditorsAmanda Lee Hughes, Fiona McNeill, Christopher W. Zobel
PublisherInformation Systems for Crisis Response and Management, ISCRAM
Pages134-141
Number of pages8
ISBN (Electronic)9781949373271
StatePublished - 2020
Event17th Annual International Conference on Information Systems for Crisis Response and Management, ISCRAM 2020 - Blacksburg, United States
Duration: May 23 2021 → …

Publication series

NameProceedings of the International ISCRAM Conference
Volume2020-May
ISSN (Electronic)2411-3387

Conference

Conference17th Annual International Conference on Information Systems for Crisis Response and Management, ISCRAM 2020
Country/TerritoryUnited States
CityBlacksburg
Period5/23/21 → …

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management
  • Electrical and Electronic Engineering

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