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Open Issues in Opinion Mining
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Author(s): Vishal Vyas (Pondicherry University, India)and V. Uma (Pondicherry University, India)
Copyright: 2019
Pages: 15
Source title:
Extracting Knowledge From Opinion Mining
Source Author(s)/Editor(s): Rashmi Agrawal (Manav Rachna International Institute of Research and Studies, India)and Neha Gupta (Manav Rachna International Institute of Research and Studies, India)
DOI: 10.4018/978-1-5225-6117-0.ch013
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Abstract
Opinions are found everywhere. In web forums like social networking websites, e-commerce sites, etc., rich user-generated content is available in large volume. Web 2.0 has made rich information easily accessible. Manual insight extraction of information from these platforms is a cumbersome task. Deriving insight from such available information is known as opinion mining (OM). Opinion mining is not a single-stage process. Text mining and natural language processing (NLP) is used to obtain information from such data. In NLP, content from the text corpus is pre-processed, opinion word is extracted, and analysis of those words is done to get the opinion. The volume of web content is increasing every day. There is a demand for more ingenious techniques, which remains a challenge in opinion mining. The efficiency of opinion mining systems has not reached the satisfactory level because of the issues in various stages of opinion mining. This chapter will explain the various research issues and challenges present in each stage of opinion mining.
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