Artificial Intelligence Applications and Innovations 12th IFIP WG 12.5 International Conference and Workshops, AIAI 2016 Thessaloniki, Greece, September 16–18, 2016
Abstract : Social media has become an important open communication medium during crises. The information shared about a crisis in social media is massive, complex, informal and heterogeneous, which makes extracting useful information a difficult task. This paper presents a first step towards an approach for information extraction from large Twitter data. In brief, we propose a Recurrent Neural Network based model for text generation able to produce a unique text capturing the general consensus of a large collection of twitter messages. The generated text is able to capture information about different crises from tens of thousand of tweets summarized only in a 2000 characters text.
https://hal.inria.fr/hal-01557644
Contributor : Hal Ifip
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Submitted on : Thursday, July 6, 2017 - 1:55:39 PM
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Mehdi Ben Lazreg, Morten Goodwin, Ole-Christoffer Granmo. Information Abstraction from Crises Related Tweets Using Recurrent Neural Network. 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2016, Thessaloniki, Greece. pp.441-452, ⟨10.1007/978-3-319-44944-9_38⟩. ⟨hal-01557644⟩
