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

@inproceedings{Htait2016LSISAS,
  title={LSIS at SemEval-2016 Task 7: Using Web Search Engines for English and Arabic Unsupervised Sentiment Intensity Prediction},
  author={Amal Htait and S{\'e}bastien Fournier and Patrice Bellot},
  booktitle={SemEval@NAACL-HLT},
  year={2016}
}
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… CONTINUE READING

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