A Survey on Sentiment Analysais Techniques
Keywords:
NLP, Sentimental Analysis, IDF, Classification, SVM, Deep Learning.Abstract
With rapid development of Web 2.0 applications such as microbloging, social networks, e-commerce sites, news portals and web-forums reviews, comments, recommendations, ratings and feedbacks are generated by users. This user generated content can be about products, people, events, etc. This information is very useful for businesses, governments and individuals. While this content meant to be helpful, bulk of this user generated content require the use of automated techniques for mining and analyzing because manual analysis are difficult for such a huge content. Sentiment analysis is the automated mining of attitudes, opinions, and emotions from text, speech, and database sources through Natural Language Processing (NLP). This paper presents a survey on the Sentiment analysis applications and challenges with their approaches and techniques.
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