Unsupervised Crisis Information Extraction from Twitter Data
Interdonato R., Doucet A., Guillaume J.L.. 2018. In : Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining ASONAM 2018. Barcelone : IEE; ACM, p. 579-580. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2018-08-28/2018-08-31, Barcelona (Espagne).
While microblogging-based Online Social Networks have become an attractive data source in emergency situations, overcoming information overload is still not trivial. We propose a framework which integrates natural language processing and clustering techniques in order to produce a ranking of relevant tweets based on their informativeness. Experiments on four Twitter collections in two languages (English and French) proved the significance of our approach.
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Agents Cirad, auteurs de cette publication :
- Interdonato Roberto — Es / UMR Tetis