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Les Signaux Sociaux émotionnels : Quel impact sur la recherche d'information ?

Abstract : A large amount of social feedback expressed by social signals (e.g. like, +1, rating) are assigned to web resources. These signals are often exploited as additional sources of evidence in search engines. Our objective in this paper is to study the impact of the new social signals, called Facebook reactions (love, haha, angry, wow, sad) in the retrieval. These reactions allow users to express more nuanced emotions compared to classic signals (e.g. like, share). First, we analyze these reactions and show how users use these signals to interact with resources (e.g. posts, video, etc). Second, we evaluate the impact of each such reaction in the retrieval, by comparing them to both the textual model without social features and the first classical signal (like-based model). These social features are modeled as document prior and are integrated into a language model. We conducted a series of experiments on INEX IMDb dataset. Our findings reveal that incorporating social features is a promising approach for improving the retrieval ranking performance.
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Submitted on : Tuesday, November 19, 2019 - 6:01:51 PM
Last modification on : Thursday, July 14, 2022 - 4:10:47 AM


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  • HAL Id : hal-01490083, version 1


Ismail Badache, Mohand Boughanem. Les Signaux Sociaux émotionnels : Quel impact sur la recherche d'information ?. Conférence en Recherche d’Information et Applications (CORIA 2017), Mar 2017, Marseille, France. ⟨hal-01490083⟩



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