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Does Dialectal Variation Matter in Term-Based Feature Selection of Sentiment Analysis?: An Investigation into Multi-dialectal Chinese Microblogs

Published: 28 June 2015 Publication History

Abstract

This paper examines the feature selection procedures of sentiment analysis on a multi-dialectal language. We analyzed a dataset with over 6 million microblogs in China, a multi-dialectal country, deployed sentiment classifier to examine the positive/negative emotion carried by the microblogs, and explored the regional variations in the optimal feature vectors. The results support a localized feature vectors in some China's regions can maximize the classification accuracy and show that geographical distance between provinces and common dialect used contribute to explaining the provincial difference in the feature vectors. This research can be applied to other multicultural countries for feature vector optimization in sentiment analysis.

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Bollen, J., Mao, H. and Zeng, X. Twitter mood predicts the stock market. Journal of Computational Science, 2, 1 2011), 1--8.
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Kurpaska, M. Chinese language (s): a look through the prism of The great dictionary of modern Chinese dialects. Walter de Gruyter, 2010.
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Fu, K. W., Chan, C. H. and Chau, M. Assessing censorship on microblogs in China: Discriminatory keyword analysis and the real-name registration policy. Internet Computing, IEEE, 17, 3 2013), 42--50.
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Lin, R. G. and Tsai, T. C. Scalable System for Textual Analysis of Stock Market Prediction. City, 2014.

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Published In

cover image ACM Conferences
WebSci '15: Proceedings of the ACM Web Science Conference
June 2015
366 pages
ISBN:9781450336727
DOI:10.1145/2786451
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 ACM 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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 June 2015

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Author Tags

  1. Chinese social media
  2. Feature selection
  3. Sentiment analysis

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  • Research-article
  • Research
  • Refereed limited

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WebSci '15
Sponsor:
WebSci '15: ACM Web Science Conference
June 28 - July 1, 2015
Oxford, United Kingdom

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Overall Acceptance Rate 245 of 933 submissions, 26%

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