LSIS at SemEval-2016 Task 7: Using Web Search Engines for English and Arabic Unsupervised Sentiment Intensity Prediction - Archive ouverte HAL Access content directly
Conference Papers Year : 2016

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

Abstract

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.
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Dates and versions

hal-01771674 , version 1 (17-05-2018)

Identifiers

  • HAL Id : hal-01771674 , version 1

Cite

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⟩
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