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Simulation of Opinion Mining in Hindi Language


Hridesh Gupta , galgotias university; Pankaj Sharma, galgotias university


Opinion Mining, Sentiment Analysis, Reviews, Hindi Language WordNet


Textual information in the world can be broadly classified into two main categories, facts and opinions. Facts are objective statements about entities and events in the world. Opinions are subjective statements that reflect people’s sentiments or perceptions about the entities and events. Sentiment analysis (also known as opinion mining) refers to the use of NLP, text analysis and computational linguistics to identify and extract subjective information in source materials. This information is unstructured, however, and because it’s produced for human consumption, it’s not something that’s machine process able. The opinions of users are helpful for the public and for stakeholders when making certain decisions. Opinion mining is a way to retrieve information through search engines, Web blogs and social networks. Because of the huge number of reviews in the form of unstructured text, it is impossible to summarize the information manually. Although commonly used interchangeably to denote the same field of study, opinion mining and sentiment analysis actually focus on polarity detection and emotion recognition, respectively Research in opinion mining mostly carried out in English language but it is very important to perform the opinion mining in Hindi language also as large amount of information in Hindi is also available on the Web.

Other Details

Paper ID: IJSRDV3I2331
Published in: Volume : 3, Issue : 2
Publication Date: 01/05/2015
Page(s): 915-917

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