A Review Paper on Twitter Sentiment Analysis Techniques
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 10
Abstract
Sentiment Analysis is growing exponentially due to the importance of the automation in mining, extracting and processing information in order to determine the general opinion of a person Hence the conventional sentiment analysis approaches fails to efficiently handle the vast amount of sentiment data available now a days.. Twitter sentiment analysis is difficult to compare with the general sentiment analysis because of the lots of slang words and incorrect spellings. The extreme limit of characters that are permitted in Twitter is 140. Lexicon based and Machine learning are the two methods used for analysis the sentiments from the content. In this paper we attempt to improve the accuracy using both techniques and Experimental results show that the proposed method dramatically improves the accuracy and outperforms the state-of-the-art baselines.
Authors and Affiliations
Jatinder Kaur
Keywords
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