More Web Proxy on the site http://driver.im/

Article

Free access

Automatic construction of polarity-tagged corpus from HTML documents

Authors:

Masaru KitsuregawaAuthors Info & Claims

COLING-ACL '06: Proceedings of the COLING/ACL on Main conference poster sessions

Pages 452 - 459

Published: 17 July 2006 Publication History

Abstract

This paper proposes a novel method of building polarity-tagged corpus from HTML documents. The characteristics of this method is that it is fully automatic and can be applied to arbitrary HTML documents. The idea behind our method is to utilize certain layout structures and linguistic pattern. By using them, we can automatically extract such sentences that express opinion. In our experiment, the method could construct a corpus consisting of 126,610 sentences.

References

[1]

Kushal Dave, Steve Lawrence, and David M. Pennock. 2003. Mining the peanut gallery: Opinion extraction and semantic classification of product revews. In Proceedings of the WWW, pages 519--528.

Digital Library

[2]

Andrea Esuli and Fabrizio Sebastiani. 2005. Determining the semantic orientation of terms throush gloss classification. In Proceedings of the CIKM.

Digital Library

[3]

Vasileios Hatzivassiloglou and Katheleen R. McKeown. 1997. Predicting the semantic orientation of adjectives. In Proceedings of the ACL, pages 174--181.

Digital Library

[4]

Minqing Hu and Bing Liu. 2004. Mining and summarizing customer reviews. In Proceedings of the KDD, pages 168--177.

Digital Library

[5]

Jaap Kamps, Maarten Marx, Robert J. Mokken, and Maarten de Rijke. 2004. Using wordnet to measure semantic orientations of adjectives. In Proceedings of the LREC.

[6]

Satoshi Morinaga, Kenji Yamanishi, Kenji Tateishi, and Toshikazu Fukushima. 2002. Mining product reputations on the web. In Proceedings of the KDD.

Digital Library

[7]

Bo Pang, Lillian Lee, and Shivakumar Vaihyanathan. 2002. Thumbs up? sentiment classification using machine learning techniques. In Proceedings of the EMNLP.

Digital Library

[8]

Ellen Riloff and Janyce Wiebe. 2003. Learning extraction patterns for subjective expressions. In Proceedings of the EMNLP.

Digital Library

[9]

Ellen Riloff, Janyce Wiebe, and Theresa Wilson. 2003. Learning subjective nouns using extraction pattern bootstrapping. In Proceedings of the CoNLL.

Digital Library

[10]

Hiroya Takamura, Takashi Inui, and Manabu Okumura. 2005. Extracting semantic orientation of words using spin model. In Proceedings of the ACL, pages 133--140.

Digital Library

[11]

Peter D. Turney. 2002. Thumbs up or thumbs down? senmantic orientation applied to unsupervised classification of reviews. In Proceedings of the ACL, pages 417--424.

Digital Library

[12]

Janyce Wiebe and Ellen Riloff. 2005. Creating subjective and objective sentence classifiers from unannotated texts. In Proceedings of the CICLing.

Digital Library

[13]

Janyce M. Wiebe. 2000. Learning subjective adjectives from corpora. In Proceedings of the AAAI.

Digital Library

[14]

Theresa Wilson, Janyce Wiebe, and Paul Hoffmann. 2005. Recognizing contextual polarity in phrase-level sentiment analysis. In Proceedings of the HLT/EMNLP.

Digital Library

[15]

Hong Yu and Yasileios Hatzivassiloglou. 2003. Towards answering opinion questions: Separating facts from opinions and identifying the polarity of opinion sentences. In Proceedings of the EMNLP.

Digital Library

Cited By

Yadollahi AShahraki AZaiane O(2017)Current State of Text Sentiment Analysis from Opinion to Emotion MiningACM Computing Surveys10.1145/305727050:2(1-33)Online publication date: 25-May-2017
https://dl.acm.org/doi/10.1145/3057270
Ali FKwak KKim Y(2016)Opinion mining based on fuzzy domain ontology and Support Vector MachineApplied Soft Computing10.1016/j.asoc.2016.06.00347:C(235-250)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1016/j.asoc.2016.06.003
Ali FKim EKim Y(2015)Type-2 fuzzy ontology-based opinion mining and information extractionApplied Intelligence10.1007/s10489-014-0609-y42:3(481-500)Online publication date: 1-Apr-2015
https://dl.acm.org/doi/10.1007/s10489-014-0609-y
Show More Cited By

Automatic construction of polarity-tagged corpus from HTML documents
1. Computing methodologies
  1. Artificial intelligence
2. Hardware
  1. Power and energy
    1. Power estimation and optimization

Recommendations

Automatic Knowledge Base Construction from Scholarly Documents
DocEng '17: Proceedings of the 2017 ACM Symposium on Document Engineering

The continuing growth of published scholarly content on the web ensures the availability of the most recent scientific findings to researchers. Scholarly documents, such as research articles, are easily accessed by using academic search engines that are ...
Automatic extraction of subcorpora based on subcategorization frames from a part-of-speech tagged corpus
ACL '98/COLING '98: Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics - Volume 1

This paper presents a method for extracting subcorpora documenting different subcategorization frames for verbs, nouns, and adjectives in the 100 mio. word British National Corpus. The extraction tool consists of a set of batch files for use with the ...
Automatic Persian WordNet construction
COLING '10: Proceedings of the 23rd International Conference on Computational Linguistics: Posters

In this paper, an automatic method for Persian WordNet construction based on Prenceton WordNet 2.1 (PWN) is introduced. The proposed approach uses Persian and English corpora as well as a bilingual dictionary in order to make a mapping between PWN ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image DL Hosted proceedings

COLING-ACL '06: Proceedings of the COLING/ACL on Main conference poster sessions

July 2006

992 pages

Publisher

Association for Computational Linguistics

United States

Publication History

Published: 17 July 2006

Qualifiers

Article

Acceptance Rates

COLING-ACL '06 Paper Acceptance Rate 126 of 126 submissions, 100%;

Overall Acceptance Rate 1,537 of 1,537 submissions, 100%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

10
Total Citations
View Citations
492
Total Downloads

Downloads (Last 12 months)33
Downloads (Last 6 weeks)1

Reflects downloads up to 19 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Yadollahi AShahraki AZaiane O(2017)Current State of Text Sentiment Analysis from Opinion to Emotion MiningACM Computing Surveys10.1145/305727050:2(1-33)Online publication date: 25-May-2017
https://dl.acm.org/doi/10.1145/3057270
Ali FKwak KKim Y(2016)Opinion mining based on fuzzy domain ontology and Support Vector MachineApplied Soft Computing10.1016/j.asoc.2016.06.00347:C(235-250)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1016/j.asoc.2016.06.003
Ali FKim EKim Y(2015)Type-2 fuzzy ontology-based opinion mining and information extractionApplied Intelligence10.1007/s10489-014-0609-y42:3(481-500)Online publication date: 1-Apr-2015
https://dl.acm.org/doi/10.1007/s10489-014-0609-y
Lin CHe YEverson RLapata M(2010)A comparative study of Bayesian models for unsupervised sentiment detectionProceedings of the Fourteenth Conference on Computational Natural Language Learning10.5555/1870568.1870586(144-152)Online publication date: 15-Jul-2010
https://dl.acm.org/doi/10.5555/1870568.1870586
Nakagawa TInui KKurohashi SKaplan R(2010)Dependency tree-based sentiment classification using CRFs with hidden variablesHuman Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics10.5555/1857999.1858119(786-794)Online publication date: 2-Jun-2010
https://dl.acm.org/doi/10.5555/1857999.1858119
Narayanan RLiu BChoudhary AKoehn PMihalcea R(2009)Sentiment analysis of conditional sentencesProceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 110.5555/1699510.1699534(180-189)Online publication date: 6-Aug-2009
https://dl.acm.org/doi/10.5555/1699510.1699534
Lin CHe YCheung DSong IChu WHu XLin J(2009)Joint sentiment/topic model for sentiment analysisProceedings of the 18th ACM conference on Information and knowledge management10.1145/1645953.1646003(375-384)Online publication date: 2-Nov-2009
https://dl.acm.org/doi/10.1145/1645953.1646003
De Saeger STorisawa KKazama JScott DUszkoreit H(2008)Looking for troubleProceedings of the 22nd International Conference on Computational Linguistics - Volume 110.5555/1599081.1599105(185-192)Online publication date: 18-Aug-2008
https://dl.acm.org/doi/10.5555/1599081.1599105
Pang BLee L(2008)Opinion Mining and Sentiment AnalysisFoundations and Trends in Information Retrieval10.1561/15000000112:1-2(1-135)Online publication date: 1-Jan-2008
https://dl.acm.org/doi/10.1561/1500000011
Ding XLiu BYu PNajork MBroder AChakrabarti S(2008)A holistic lexicon-based approach to opinion miningProceedings of the 2008 International Conference on Web Search and Data Mining10.1145/1341531.1341561(231-240)Online publication date: 11-Feb-2008
https://dl.acm.org/doi/10.1145/1341531.1341561

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents