Abstract
Sentiment Analysis (SA) is the utmost progressive research field in natural language processing that focuses on identifying the emotions of a writer behind the series of words and classifies public attitude, opinion from visuals, audios and texts. This paper categorizes and presents a refined study of recently published articles related with sentiment analysis research. It demonstrates an outline of the prime issues and challenges, explores sentiment resources and discusses practical techniques and tools practiced in this context. It also provides an insight of various sentiment analysis applications in several different scenarios, current enhancements and describes the possible future directions for deeper understanding of human emotions.
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