@inproceedings{jadi-etal-2016-evaluating,
title = "Evaluating Lexical Similarity to build Sentiment Similarity",
author = "Jadi, Gr{\'e}goire and
Claveau, Vincent and
Daille, B{\'e}atrice and
Monceaux, Laura",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Goggi, Sara and
Grobelnik, Marko and
Maegaard, Bente and
Mariani, Joseph and
Mazo, Helene and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}'16)",
month = may,
year = "2016",
address = "Portoro{\v{z}}, Slovenia",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/L16-1190",
pages = "1196--1201",
abstract = "In this article, we propose to evaluate the lexical similarity information provided by word representations against several opinion resources using traditional Information Retrieval tools. Word representation have been used to build and to extend opinion resources such as lexicon, and ontology and their performance have been evaluated on sentiment analysis tasks. We question this method by measuring the correlation between the sentiment proximity provided by opinion resources and the semantic similarity provided by word representations using different correlation coefficients. We also compare the neighbors found in word representations and list of similar opinion words. Our results show that the proximity of words in state-of-the-art word representations is not very effective to build sentiment similarity.",
}
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<abstract>In this article, we propose to evaluate the lexical similarity information provided by word representations against several opinion resources using traditional Information Retrieval tools. Word representation have been used to build and to extend opinion resources such as lexicon, and ontology and their performance have been evaluated on sentiment analysis tasks. We question this method by measuring the correlation between the sentiment proximity provided by opinion resources and the semantic similarity provided by word representations using different correlation coefficients. We also compare the neighbors found in word representations and list of similar opinion words. Our results show that the proximity of words in state-of-the-art word representations is not very effective to build sentiment similarity.</abstract>
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%0 Conference Proceedings
%T Evaluating Lexical Similarity to build Sentiment Similarity
%A Jadi, Grégoire
%A Claveau, Vincent
%A Daille, Béatrice
%A Monceaux, Laura
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Grobelnik, Marko
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Helene
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)
%D 2016
%8 May
%I European Language Resources Association (ELRA)
%C Portorož, Slovenia
%F jadi-etal-2016-evaluating
%X In this article, we propose to evaluate the lexical similarity information provided by word representations against several opinion resources using traditional Information Retrieval tools. Word representation have been used to build and to extend opinion resources such as lexicon, and ontology and their performance have been evaluated on sentiment analysis tasks. We question this method by measuring the correlation between the sentiment proximity provided by opinion resources and the semantic similarity provided by word representations using different correlation coefficients. We also compare the neighbors found in word representations and list of similar opinion words. Our results show that the proximity of words in state-of-the-art word representations is not very effective to build sentiment similarity.
%U https://aclanthology.org/L16-1190
%P 1196-1201
Markdown (Informal)
[Evaluating Lexical Similarity to build Sentiment Similarity](https://aclanthology.org/L16-1190) (Jadi et al., LREC 2016)
ACL
- Grégoire Jadi, Vincent Claveau, Béatrice Daille, and Laura Monceaux. 2016. Evaluating Lexical Similarity to build Sentiment Similarity. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 1196–1201, Portorož, Slovenia. European Language Resources Association (ELRA).