LSIS at SemEval-2016 Task 7: Using Web Search Engines for English and Arabic Unsupervised Sentiment Intensity Prediction

Amal Htait (1, 2) , Sébastien Fournier (1, 3) , Patrice Bellot (1)

1 LIS - Laboratoire d'Informatique et des Systèmes (LIS) (Marseille, Toulon)
2 CLEO - Centre pour l'édition électronique ouverte
3 R2I - Recherche d’information et Interactions

In this paper, we present our contribution in SemEval2016 task7 1 : Determining Sentiment Intensity of English and Arabic Phrases, where we use web search engines for English and Arabic unsupervised sentiment intensity prediction. Our work is based, first, on a group of classic sentiment lexicons (e.g. Sen-timent140 Lexicon, SentiWordNet). Second, on web search engines' ability to find the co-occurrence of sentences with predefined negative and positive words. The use of web search engines (e.g. Google Search API) enhance the results on phrases built from opposite polarity terms.

Domaines: Informatique [cs]; Informatique et langage [cs.CL]; Traitement du texte et du document; Recherche d'information [cs.IR]

Amal Htait, Sébastien Fournier, Patrice Bellot. LSIS at SemEval-2016 Task 7: Using Web Search Engines for English and Arabic Unsupervised Sentiment Intensity Prediction. 10th International Workshop on Semantic Evaluation (SemEval-2016), Jun 2016, San Diego, United States. pp.469 - 473. ⟨hal-01771674⟩