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SENTIMENT ANALYSIS: A REVIEW
Abstract
This paper compared research solely related to sentiment analysis. Various different approaches are compared based on the research work the authors have published. Sentiment analysis can be done on attitudes, reviews and sentiments. The sentiment analysis is done by first normalizing the data & then selecting the vocabulary to be used to find difference in the given text. Now the algorithm based on the user specification can be decided to extract the feature of the given text.
References
A clustering and opinion mining approach to socio-political analysis of the blogosphere in ICCIC 2010 by Singh and Vivek Kumar.
Sentiment Analysis and Opinion Mining in Morgan & Claypool Publishers, 2012 by Bing Liu.
Analysis of different approaches to Sentence-Level Sentiment Classification in IJSET 2013 by V. S. Jagtap and Karishma Pawar.
A Comparison of Document, Sentence, and Term Event Spaces in IEEE 2010 by Catherine Blake.
A semantic Based Information Retrieval Model for Blog in IEEE 2010 by Ying Chen, Wenping Guo, Xiaoming Zhao.
Citius: A Naive-Bayes Strategy for Sentiment Analysis on English Tweets in SemEval 2014 by Pablo Gamallo and Marcos Garcia.
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