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Sentiment Classification of Stock Comments in Chinese Based on Semi-Supervised Approach Correcting with Feedback Information

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This paper proposes a sentiment classification approach of stock comments in Chinese, which is a new research field of text polarity analysis. Method in this paper firstly uses a semi-supervised text categorization approach based on bootstrapping to solve the classification; Secondly, because not every portion of a document has the same polarity with the overall sentiment of the document, so a correcting step with feedback information is added into this approach. The results show that statistical method can work well without lexicon on sentiment classification of stock comments in Chinese, and the feedback information can improve the result to a certain extent.
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Document Type: Research Article

Publication date: March 1, 2012

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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