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        <title>Adapted Sentiment Similarity Seed Words For French Tweets’ Polarity Classification</title>
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        <name type="personal">
            <namePart type="given">Pascale</namePart>
            <namePart type="family">Sébillot</namePart>
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        <name type="personal">
            <namePart type="given">Vincent</namePart>
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    <abstract>We present, in this paper, our contribution in DEFT 2018 task 2 : “Global polarity”, determining the overall polarity (Positive, Negative, Neutral or MixPosNeg) of tweets regarding public transport, in French language. Our system is based on a list of sentiment seed-words adapted for French public transport tweets. These seed-words are extracted from DEFT’s training annotated dataset, and the sentiment relations between seed-words and other terms are captured by cosine measure of their word embeddings representations, using a French language word embeddings model of 683k words. Our semi-supervised system achieved an F1-measure equals to 0.64.</abstract>
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%0 Conference Proceedings
%T Adapted Sentiment Similarity Seed Words For French Tweets’ Polarity Classification
%A Htait, Amal
%Y Sébillot, Pascale
%Y Claveau, Vincent
%S Actes de la Conférence TALN. Volume 2 - Démonstrations, articles des Rencontres Jeunes Chercheurs, ateliers DeFT
%D 2018
%8 May
%I ATALA
%C Rennes, France
%F htait-2018-adapted
%X We present, in this paper, our contribution in DEFT 2018 task 2 : “Global polarity”, determining the overall polarity (Positive, Negative, Neutral or MixPosNeg) of tweets regarding public transport, in French language. Our system is based on a list of sentiment seed-words adapted for French public transport tweets. These seed-words are extracted from DEFT’s training annotated dataset, and the sentiment relations between seed-words and other terms are captured by cosine measure of their word embeddings representations, using a French language word embeddings model of 683k words. Our semi-supervised system achieved an F1-measure equals to 0.64.
%U https://aclanthology.org/2018.jeptalnrecital-deft.12
%P 323-328

Markdown (Informal)

[Adapted Sentiment Similarity Seed Words For French Tweets’ Polarity Classification](https://aclanthology.org/2018.jeptalnrecital-deft.12) (Htait, JEP/TALN/RECITAL 2018)

• Adapted Sentiment Similarity Seed Words For French Tweets’ Polarity Classification (Htait, JEP/TALN/RECITAL 2018)

ACL

• Amal Htait. 2018. Adapted Sentiment Similarity Seed Words For French Tweets’ Polarity Classification. In Actes de la Conférence TALN. Volume 2 - Démonstrations, articles des Rencontres Jeunes Chercheurs, ateliers DeFT, pages 323–328, Rennes, France. ATALA.