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Feature Selection for Sentiment Classification Using Matrix Factorization

Authors:

Jiguang Liang,

Xiaofei Zhou,

Li Guo,

Shuo BaiAuthors Info & Claims

WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web

Pages 63 - 64

https://doi.org/10.1145/2740908.2742741

Published: 18 May 2015 Publication History

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Abstract

Feature selection is a critical task in both sentiment classification and topical text classification. However, most existing feature selection algorithms ignore a significant contextual difference between them that sentiment classification is commonly depended more on the words conveying sentiments. Based on this observation, a new feature selection method based on matrix factorization is proposed to identify the words with strong inter-sentiment distinguish-ability and intra-sentiment similarity. Furthermore, experiments show that our models require less features while still maintaining reasonable classification accuracy.

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Cited By

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Chelmis CZois D(2021)Dynamic, Incremental, and Continuous Detection of Cyberbullying in Online Social MediaACM Transactions on the Web10.1145/344801415:3(1-33)Online publication date: 13-May-2021
https://dl.acm.org/doi/10.1145/3448014
Pintas JFernandes LGarcia A(2021)Feature selection methods for text classification: a systematic literature reviewArtificial Intelligence Review10.1007/s10462-021-09970-6Online publication date: 24-Feb-2021
https://doi.org/10.1007/s10462-021-09970-6
Yao MChelmis CZois D(2019)Cyberbullying Ends Here: Towards Robust Detection of Cyberbullying in Social MediaThe World Wide Web Conference10.1145/3308558.3313462(3427-3433)Online publication date: 13-May-2019
https://dl.acm.org/doi/10.1145/3308558.3313462
Show More Cited By

Index Terms

Feature Selection for Sentiment Classification Using Matrix Factorization
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources

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Published In

WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web

May 2015

1602 pages

ISBN:9781450334730

DOI:10.1145/2740908

General Chairs:
Aldo Gangemi
National Research Council, Italy & Paris 13 University-CNRS, France
,
Stefano Leonardi
Sapienza University of Rome, Italy
,
Alessandro Panconesi
Sapienza University of Rome, Italy

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 May 2015

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Funding Sources

National Nature Science Foundation of China
Strategic Priority Research Program of Chinese Academy of Sciences

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WWW '15

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IW3C2

WWW '15: 24th International World Wide Web Conference

May 18 - 22, 2015

Florence, Italy

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Chelmis CZois D(2021)Dynamic, Incremental, and Continuous Detection of Cyberbullying in Online Social MediaACM Transactions on the Web10.1145/344801415:3(1-33)Online publication date: 13-May-2021
https://dl.acm.org/doi/10.1145/3448014
Pintas JFernandes LGarcia A(2021)Feature selection methods for text classification: a systematic literature reviewArtificial Intelligence Review10.1007/s10462-021-09970-6Online publication date: 24-Feb-2021
https://doi.org/10.1007/s10462-021-09970-6
Yao MChelmis CZois D(2019)Cyberbullying Ends Here: Towards Robust Detection of Cyberbullying in Social MediaThe World Wide Web Conference10.1145/3308558.3313462(3427-3433)Online publication date: 13-May-2019
https://dl.acm.org/doi/10.1145/3308558.3313462
Xu QZhu LDai TGuo LCao S(2019)Non-negative matrix factorization for implicit aspect identificationJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-019-01328-911:7(2683-2699)Online publication date: 29-May-2019
https://doi.org/10.1007/s12652-019-01328-9
Benamara FTaboada MMathieu Y(2017)Evaluative language beyond bags of wordsComputational Linguistics10.1162/COLI_a_0027843:1(201-264)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1162/COLI_a_00278
Zhao CWang SLi D(2016)Determining Fuzzy Membership for Sentiment Classification: A Three-Layer Sentiment Propagation ModelPLOS ONE10.1371/journal.pone.016556011:11(e0165560)Online publication date: 15-Nov-2016
https://doi.org/10.1371/journal.pone.0165560
Liu ZLiu SLiu LSun JPeng XWang T(2016)Sentiment recognition of online course reviews using multi-swarm optimization-based selected featuresNeurocomputing10.1016/j.neucom.2015.12.036185:C(11-20)Online publication date: 12-Apr-2016
https://dl.acm.org/doi/10.1016/j.neucom.2015.12.036

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Sentiment Lexicon Enhanced Neural Sentiment Classification

Domain-specific sentiment analysis using contextual feature generation

Sentiment classification: a combination of PMI, sentiwordnet and fuzzy function

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