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http://dx.doi.org/10.7236/JIIBC.2013.13.5.27

Automatic Retrieval of SNS Opinion Document Using Machine Learning Technique  

Chang, Jae-Young (Dept. of Computer Engineering, Hansung University)
Publication Information
The Journal of the Institute of Internet, Broadcasting and Communication / v.13, no.5, 2013 , pp. 27-35 More about this Journal
Abstract
Recently, as Social Network Services(SNS) are becoming more popular, much research has been doing on analyzing public opinions from SNS. One of the most important tasks for solving such a problem is to separate opinion(subjective) documents from others(e.g. objective documents) in SNS. In this paper, we propose a new method of retrieving the opinion documents from Twitter. The reason why it is not easy to search or classify the opinion documents in Twitter is due to a lack of publicly available Twitter documents for training. To tackle the problem, at first, we build a machine-learned model for sentiment classification using the external documents similar to Twitter, and then modify the model to separate the opinion documents from Twitter. Experimental results show that proposed method can be applied successfully in opinion classification.
Keywords
Opinion Document; Social Network Service; Twitter; Machine Learning; Sentiment Classification;
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