senti.ue-en: an approach for informally written short texts in semeval-2013 sentiment analysis task

Bibliographic Details
Main Author: Saias, jose
Publication Date: 2013
Other Authors: Fernandes, Hilário
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10174/10342
Summary: This article describes a Sentiment Analysis (SA) system named senti.ue-en, built for participation in SemEval-2013 Task 2, a Twitter SA challenge. In both challenge subtasks we used the same supervised machine learning approach, including two classifiers in pipeline, with 22 semantic oriented features, such as polarized term presence and index, and negation presence. Our system achieved a better score on Task A (0.7413) than in the Task B (0.4785). In the first subtask, there is a better result for SMS than the obtained for the more trained type of data, the tweets.
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spelling senti.ue-en: an approach for informally written short texts in semeval-2013 sentiment analysis taskopinion miningsentiment analysisNLPMachine LearningThis article describes a Sentiment Analysis (SA) system named senti.ue-en, built for participation in SemEval-2013 Task 2, a Twitter SA challenge. In both challenge subtasks we used the same supervised machine learning approach, including two classifiers in pipeline, with 22 semantic oriented features, such as polarized term presence and index, and negation presence. Our system achieved a better score on Task A (0.7413) than in the Task B (0.4785). In the first subtask, there is a better result for SMS than the obtained for the more trained type of data, the tweets.Association for Computational Linguistics2014-01-29T17:55:18Z2014-01-292013-06-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/10342http://hdl.handle.net/10174/10342engJosé Saias and Hilário Fernandes. senti.ue-en: an approach for informally written short texts in semeval-2013 sentiment analysis task. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013), pages 508-512, Atlanta, Georgia, USA, June 2013. Association for Computational Linguisticshttp://aclweb.org/anthology//S/S13/S13-2084.pdfjsaias@uevora.pthilario.fernandes@cortex-intelligence.com283Saias, joseFernandes, Hilárioinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-01-03T18:53:03Zoai:dspace.uevora.pt:10174/10342Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T12:00:58.510270Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv senti.ue-en: an approach for informally written short texts in semeval-2013 sentiment analysis task
title senti.ue-en: an approach for informally written short texts in semeval-2013 sentiment analysis task
spellingShingle senti.ue-en: an approach for informally written short texts in semeval-2013 sentiment analysis task
Saias, jose
opinion mining
sentiment analysis
NLP
Machine Learning
title_short senti.ue-en: an approach for informally written short texts in semeval-2013 sentiment analysis task
title_full senti.ue-en: an approach for informally written short texts in semeval-2013 sentiment analysis task
title_fullStr senti.ue-en: an approach for informally written short texts in semeval-2013 sentiment analysis task
title_full_unstemmed senti.ue-en: an approach for informally written short texts in semeval-2013 sentiment analysis task
title_sort senti.ue-en: an approach for informally written short texts in semeval-2013 sentiment analysis task
author Saias, jose
author_facet Saias, jose
Fernandes, Hilário
author_role author
author2 Fernandes, Hilário
author2_role author
dc.contributor.author.fl_str_mv Saias, jose
Fernandes, Hilário
dc.subject.por.fl_str_mv opinion mining
sentiment analysis
NLP
Machine Learning
topic opinion mining
sentiment analysis
NLP
Machine Learning
description This article describes a Sentiment Analysis (SA) system named senti.ue-en, built for participation in SemEval-2013 Task 2, a Twitter SA challenge. In both challenge subtasks we used the same supervised machine learning approach, including two classifiers in pipeline, with 22 semantic oriented features, such as polarized term presence and index, and negation presence. Our system achieved a better score on Task A (0.7413) than in the Task B (0.4785). In the first subtask, there is a better result for SMS than the obtained for the more trained type of data, the tweets.
publishDate 2013
dc.date.none.fl_str_mv 2013-06-01T00:00:00Z
2014-01-29T17:55:18Z
2014-01-29
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10174/10342
http://hdl.handle.net/10174/10342
url http://hdl.handle.net/10174/10342
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv José Saias and Hilário Fernandes. senti.ue-en: an approach for informally written short texts in semeval-2013 sentiment analysis task. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013), pages 508-512, Atlanta, Georgia, USA, June 2013. Association for Computational Linguistics
http://aclweb.org/anthology//S/S13/S13-2084.pdf
jsaias@uevora.pt
hilario.fernandes@cortex-intelligence.com
283
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Association for Computational Linguistics
publisher.none.fl_str_mv Association for Computational Linguistics
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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