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Various Techniques for Sentiment Analysis of Products Review – A Review
Author(s) -
Anjani Chanji,
Rekha Bhatia
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016910422
Subject(s) - computer science , sentiment analysis , data science , information retrieval , artificial intelligence
sentiment analysis is the analysis of the sentiment in the numeric form from the given text input. The text data obtained from the social networks primarily undergoes the emotion mining method to analyze the sentiment of the user messages posted online. The best known sentiment analysis approaches are supervised approaches and utilizes the dictionary with pre-enlisted sentiment weights to evaluate the overall weight of the sentence sentiment. The pre-enlisted sentiment weights are computed in the linguistic dictionaries such as WordNet by Princeton University, SenticNet by MIT andHindi SentiWordnet by IIT Bombay. The appropriate dictionaries areutilized to evaluate the sentiment of the input text data for the social threads, product review, opinion mining, etc.This work focuses upon the detailed literature study over the sentiment analysis and concludes the shortcomings of the existing models to improve the design of the sentiment analysis models Keywordsanalysis, Product review classification, Porter stemming, Quick response, Opinion mining.

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