@inproceedings{vilares-etal-2016-en,
title = "{EN}-{ES}-{CS}: An {E}nglish-{S}panish Code-Switching {T}witter Corpus for Multilingual Sentiment Analysis",
author = "Vilares, David and
Alonso, Miguel A. and
G{\'o}mez-Rodr{\'\i}guez, Carlos",
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/L16-1655",
pages = "4149--4153",
abstract = "Code-switching texts are those that contain terms in two or more different languages, and they appear increasingly often in social media. The aim of this paper is to provide a resource to the research community to evaluate the performance of sentiment classification techniques on this complex multilingual environment, proposing an English-Spanish corpus of tweets with code-switching (EN-ES-CS CORPUS). The tweets are labeled according to two well-known criteria used for this purpose: SentiStrength and a trinary scale (positive, neutral and negative categories). Preliminary work on the resource is already done, providing a set of baselines for the research community.",
}
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%0 Conference Proceedings
%T EN-ES-CS: An English-Spanish Code-Switching Twitter Corpus for Multilingual Sentiment Analysis
%A Vilares, David
%A Alonso, Miguel A.
%A Gómez-Rodríguez, Carlos
%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 vilares-etal-2016-en
%X Code-switching texts are those that contain terms in two or more different languages, and they appear increasingly often in social media. The aim of this paper is to provide a resource to the research community to evaluate the performance of sentiment classification techniques on this complex multilingual environment, proposing an English-Spanish corpus of tweets with code-switching (EN-ES-CS CORPUS). The tweets are labeled according to two well-known criteria used for this purpose: SentiStrength and a trinary scale (positive, neutral and negative categories). Preliminary work on the resource is already done, providing a set of baselines for the research community.
%U https://aclanthology.org/L16-1655
%P 4149-4153
Markdown (Informal)
[EN-ES-CS: An English-Spanish Code-Switching Twitter Corpus for Multilingual Sentiment Analysis](https://aclanthology.org/L16-1655) (Vilares et al., LREC 2016)
ACL