Classification of attitude words for opinion mining

This work details appraisal extraction from attitude expressions. Here, by attitude expressions, we refer to those single words that convey the evaluation of sentiments or emotional states, about human behaviors, objects, processes or people, according to the Appraisal Theory of language. The attitu...

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Detalles Bibliográficos
Autores: LARITZA HERNANDEZ ROJAS, AURELIO LOPEZ LOPEZ
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2011
País:México
Institución:Instituto Nacional de Astrofísica, Óptica y Electrónica
Repositorio:Repositorio Institucional del INAOE
Idioma:inglés
OAI Identifier:oai:inaoe.repositorioinstitucional.mx:1009/1671
Acceso en línea:http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1671
Access Level:acceso abierto
Palabra clave:info:eu-repo/classification/Opinion Extraction/Opinion Extraction
info:eu-repo/classification/Appraisal Theory/Appraisal Theory
info:eu-repo/classification/Corpus Evaluation/Corpus Evaluation
info:eu-repo/classification/Machine Learning/Machine Learning
info:eu-repo/classification/cti/1
info:eu-repo/classification/cti/12
info:eu-repo/classification/cti/1203
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spelling Classification of attitude words for opinion miningLARITZA HERNANDEZ ROJASAURELIO LOPEZ LOPEZinfo:eu-repo/classification/Opinion Extraction/Opinion Extractioninfo:eu-repo/classification/Appraisal Theory/Appraisal Theoryinfo:eu-repo/classification/Corpus Evaluation/Corpus Evaluationinfo:eu-repo/classification/Machine Learning/Machine Learninginfo:eu-repo/classification/cti/1info:eu-repo/classification/cti/12info:eu-repo/classification/cti/1203info:eu-repo/classification/cti/1203This work details appraisal extraction from attitude expressions. Here, by attitude expressions, we refer to those single words that convey the evaluation of sentiments or emotional states, about human behaviors, objects, processes or people, according to the Appraisal Theory of language. The attitude words can be classified into affect, judgment, and appreciation; either positive or negative. Extraction of the attitude words has a significant range of applications from opinion extraction and summarization, up to temporal opinion analysis. To determine the attitude, we use two machine learning techniques; namely, Support Vector Machines and Random Forest. These algorithms classify a given word starting from a vector that represents the information from the context where the words tend to occur. On the other hand, we can observe the context of the words relying on a corpus of sentences from user generated contents, such as reviews, editorials and other online texts.IJCLA2011info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttp://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1671reponame:Repositorio Institucional del INAOEinstname:Instituto Nacional de Astrofísica, Óptica y Electrónicainstacron:INAOEengcitation:Hernadez-Rojas, L., et al., (2011). Classification of attitude words for opinion mining, IJCLA, Vol. 2 (1–2): 267–283info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0oai:inaoe.repositorioinstitucional.mx:1009/16712024-08-28T03:22:59Z
dc.title.none.fl_str_mv Classification of attitude words for opinion mining
title Classification of attitude words for opinion mining
spellingShingle Classification of attitude words for opinion mining
LARITZA HERNANDEZ ROJAS
info:eu-repo/classification/Opinion Extraction/Opinion Extraction
info:eu-repo/classification/Appraisal Theory/Appraisal Theory
info:eu-repo/classification/Corpus Evaluation/Corpus Evaluation
info:eu-repo/classification/Machine Learning/Machine Learning
info:eu-repo/classification/cti/1
info:eu-repo/classification/cti/12
info:eu-repo/classification/cti/1203
info:eu-repo/classification/cti/1203
title_short Classification of attitude words for opinion mining
title_full Classification of attitude words for opinion mining
title_fullStr Classification of attitude words for opinion mining
title_full_unstemmed Classification of attitude words for opinion mining
title_sort Classification of attitude words for opinion mining
dc.creator.none.fl_str_mv LARITZA HERNANDEZ ROJAS
AURELIO LOPEZ LOPEZ
author LARITZA HERNANDEZ ROJAS
author_facet LARITZA HERNANDEZ ROJAS
AURELIO LOPEZ LOPEZ
author_role author
author2 AURELIO LOPEZ LOPEZ
author2_role author
dc.subject.none.fl_str_mv info:eu-repo/classification/Opinion Extraction/Opinion Extraction
info:eu-repo/classification/Appraisal Theory/Appraisal Theory
info:eu-repo/classification/Corpus Evaluation/Corpus Evaluation
info:eu-repo/classification/Machine Learning/Machine Learning
info:eu-repo/classification/cti/1
info:eu-repo/classification/cti/12
info:eu-repo/classification/cti/1203
info:eu-repo/classification/cti/1203
topic info:eu-repo/classification/Opinion Extraction/Opinion Extraction
info:eu-repo/classification/Appraisal Theory/Appraisal Theory
info:eu-repo/classification/Corpus Evaluation/Corpus Evaluation
info:eu-repo/classification/Machine Learning/Machine Learning
info:eu-repo/classification/cti/1
info:eu-repo/classification/cti/12
info:eu-repo/classification/cti/1203
info:eu-repo/classification/cti/1203
description This work details appraisal extraction from attitude expressions. Here, by attitude expressions, we refer to those single words that convey the evaluation of sentiments or emotional states, about human behaviors, objects, processes or people, according to the Appraisal Theory of language. The attitude words can be classified into affect, judgment, and appreciation; either positive or negative. Extraction of the attitude words has a significant range of applications from opinion extraction and summarization, up to temporal opinion analysis. To determine the attitude, we use two machine learning techniques; namely, Support Vector Machines and Random Forest. These algorithms classify a given word starting from a vector that represents the information from the context where the words tend to occur. On the other hand, we can observe the context of the words relying on a corpus of sentences from user generated contents, such as reviews, editorials and other online texts.
publishDate 2011
dc.date.none.fl_str_mv 2011
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1671
url http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1671
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv citation:Hernadez-Rojas, L., et al., (2011). Classification of attitude words for opinion mining, IJCLA, Vol. 2 (1–2): 267–283
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-nd/4.0
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IJCLA
publisher.none.fl_str_mv IJCLA
dc.source.none.fl_str_mv reponame:Repositorio Institucional del INAOE
instname:Instituto Nacional de Astrofísica, Óptica y Electrónica
instacron:INAOE
instname_str Instituto Nacional de Astrofísica, Óptica y Electrónica
instacron_str INAOE
institution INAOE
reponame_str Repositorio Institucional del INAOE
collection Repositorio Institucional del INAOE
repository.name.fl_str_mv
repository.mail.fl_str_mv
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