Recherche d'Information Sociale en Langue Arabe : Cas de Facebook

Abstract : This paper proposes an approach on Facebook Search in Arabic language, which exploits all traces of users (e.g. polarity, share, like, haha) left on Facebook publications to estimate their social importance. Our goal is to show how these signals can play a vital role in improving Arabic Facebook search. First, the identification of the polarities (positive or negative) carried by the textual signals (e.g. comments) and non-textual ones (e.g. the reactions love and sad) for a given Facebook publication. Therefore, the polarity of each comment expressed on a given Facebook post, is estimated on the basis of a neural model of sentiment in Arabic language. Secondly, grouping signals according to their complementarity using selection algorithms. Third, the application of learning to rank algorithms to re-rank Facebook search results based on the selected groups of signals. Finally, experiments are carried out on 13500 Face-book posts, collected from 45 topics in Arabic language. Experiments reveal promising results.
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Contributor : Ismail Badache <>
Submitted on : Wednesday, March 20, 2019 - 9:43:37 AM
Last modification on : Thursday, April 4, 2019 - 1:50:18 AM
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  • HAL Id : hal-02073618, version 1


Ismail Badache, Aya Abu-Thaher, Mariam Hamdan, Lara Abu-Jaish. Recherche d'Information Sociale en Langue Arabe : Cas de Facebook. COnférence en Recherche d'Information et Applications, Mar 2019, Lyon, France. ⟨hal-02073618⟩



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