Partially Supervised Phrase-Level Sentiment Classification

Authors:
Sang-Hyob Nam;Seung-Hoon Na;Jungi Kim;Yeha Lee;Jong-Hyeok Lee
Affiliations:
Division of Electrical and Computer Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea 790---784;Division of Electrical and Computer Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea 790---784;Division of Electrical and Computer Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea 790---784;Division of Electrical and Computer Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea 790---784;Division of Electrical and Computer Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea 790---784
Venue:
ICCPOL '09 Proceedings of the 22nd International Conference on Computer Processing of Oriental Languages. Language Technology for the Knowledge-based Economy
Year:
2009

Citing 11
Cited 0

Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data

ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Measuring praise and criticism: Inference of semantic orientation from association

ACM Transactions on Information Systems (TOIS)
Sentiment analysis: capturing favorability using natural language processing

Proceedings of the 2nd international conference on Knowledge capture
Predicting the semantic orientation of adjectives

ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Sentiment Classification Using Phrase Patterns

CIT '04 Proceedings of the The Fourth International Conference on Computer and Information Technology
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews

ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Determining the semantic orientation of terms through gloss classification

Proceedings of the 14th ACM international conference on Information and knowledge management
Thumbs up?: sentiment classification using machine learning techniques

EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts

ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Recognizing contextual polarity in phrase-level sentiment analysis

HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Identifying expressions of opinion in context

IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a new partially supervised approach to phrase-level sentiment analysis that first automatically constructs a polarity-tagged corpus and then learns sequential sentiment tag from the corpus. This approach uses only sentiment sentences which are readily available on the Internet and does not use a polarity-tagged corpus which is hard to construct manually. With this approach, the system is able to automatically classify phrase-level sentiment. The result shows that a system can learn sentiment expressions without a polarity-tagged corpus.