short-paper

Supervised polarity classification of Spanish tweets based on linguistic knowledge

Authors:

Miguel Ángel Alonso,

Carlos Gómez-RodríguezAuthors Info & Claims

DocEng '13: Proceedings of the 2013 ACM symposium on Document engineering

Pages 169 - 172

https://doi.org/10.1145/2494266.2494300

Published: 10 September 2013 Publication History

Abstract

We describe a system that classifies the polarity of Spanish tweets. We adopt a hybrid approach, which combines machine learning and linguistic knowledge acquired by means of NLP. We use part-of-speech tags, syntactic dependencies and semantic knowledge as features for a supervised classifier. Lexical particularities of the language used in Twitter are taken into account in a pre-processing step. Experimental results improve over those of pure machine learning approaches and confirm the practical utility of the proposal.

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Cited By

Osorio Angel SPeña Pérez Negrón AEspinoza-Valdez A(2021)Systematic literature review of sentiment analysis in the Spanish languageData Technologies and Applications10.1108/DTA-09-2020-020055:4(461-479)Online publication date: 16-Feb-2021
https://doi.org/10.1108/DTA-09-2020-0200
García-Mendoza CGambino OVillarreal-Cervantes MCalvo H(2020)Evolutionary Optimization of Ensemble Learning to Determine Sentiment Polarity in an Unbalanced Multiclass CorpusEntropy10.3390/e2209102022:9(1020)Online publication date: 12-Sep-2020
https://doi.org/10.3390/e22091020
Vilares DThelwall MAlonso M(2015)The megaphone of the people? Spanish SentiStrength for real-time analysis of political tweetsJournal of Information Science10.1177/016555151559892641:6(799-813)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1177/0165551515598926
Show More Cited By

Index Terms

Supervised polarity classification of Spanish tweets based on linguistic knowledge
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources
2. Information systems
  1. Information retrieval
    1. Document representation
      1. Content analysis and feature selection

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Published In

cover image ACM Conferences

DocEng '13: Proceedings of the 2013 ACM symposium on Document engineering

September 2013

582 pages

ISBN:9781450317894

DOI:10.1145/2494266

Conference Chair:
Simone Marinai
University of Florence, Italy
,
Program Chair:
Kim Marriott
Monash University, Australia

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 10 September 2013

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DocEng '13

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DocEng '13: ACM Symposium on Document Engineering 2013

September 10 - 13, 2013

Florence, Italy

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DocEng '13 Paper Acceptance Rate 16 of 50 submissions, 32%;

Overall Acceptance Rate 194 of 564 submissions, 34%

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Cited By

Osorio Angel SPeña Pérez Negrón AEspinoza-Valdez A(2021)Systematic literature review of sentiment analysis in the Spanish languageData Technologies and Applications10.1108/DTA-09-2020-020055:4(461-479)Online publication date: 16-Feb-2021
https://doi.org/10.1108/DTA-09-2020-0200
García-Mendoza CGambino OVillarreal-Cervantes MCalvo H(2020)Evolutionary Optimization of Ensemble Learning to Determine Sentiment Polarity in an Unbalanced Multiclass CorpusEntropy10.3390/e2209102022:9(1020)Online publication date: 12-Sep-2020
https://doi.org/10.3390/e22091020
Vilares DThelwall MAlonso M(2015)The megaphone of the people? Spanish SentiStrength for real-time analysis of political tweetsJournal of Information Science10.1177/016555151559892641:6(799-813)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1177/0165551515598926
Cervantes OGutiérrez FGutiérrez ECastillo ESánchez JWan WSánchez JRodríguez LFortes R(2015)ExpressionProceedings of the Latin American Conference on Human Computer Interaction10.1145/2824893.2824903(1-8)Online publication date: 18-Nov-2015
https://dl.acm.org/doi/10.1145/2824893.2824903
Gutiérrez ECervantes OBáez-López DAlfredo Sánchez J(2015)Sentiment Groups as Features of a Classification Model Using a Spanish Sentiment LexiconProceedings of the 7th Mexican Conference on Pattern Recognition - Volume 911610.1007/978-3-319-19264-2_25(258-268)Online publication date: 24-Jun-2015
https://dl.acm.org/doi/10.1007/978-3-319-19264-2_25
Vilares DAlonso MGómez-Rodríguez C(2015)On the usefulness of lexical and syntactic processing in polarity classification of Twitter messagesJournal of the Association for Information Science and Technology10.1002/asi.2328466:9(1799-1816)Online publication date: 1-Sep-2015
https://dl.acm.org/doi/10.1002/asi.23284
Vilares DAlonso MGómez-Rodríguez C(2014)A linguistic approach for determining the topics of Spanish Twitter messagesJournal of Information Science10.1177/016555151456165241:2(127-145)Online publication date: 12-Dec-2014
https://doi.org/10.1177/0165551514561652

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