Adapted Sentiment Similarity Seed Words For French Tweets’ Polarity Classification

Amal Htait


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.
Anthology ID:
2018.jeptalnrecital-deft.12
Volume:
Actes de la Conférence TALN. Volume 2 - Démonstrations, articles des Rencontres Jeunes Chercheurs, ateliers DeFT
Month:
5
Year:
2018
Address:
Rennes, France
Venue:
JEP/TALN/RECITAL
SIG:
Publisher:
ATALA
Note:
Pages:
323–328
Language:
URL:
https://www.aclweb.org/anthology/2018.jeptalnrecital-deft.12
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2018.jeptalnrecital-deft.12.pdf