An Empirical Analysis on Various Techniques Used to Detect the Polarity of Customer Satisfaction in Sentiment Analysis

Abstract

Sentiment analysis is an emerging application of NLP (Natural Language Processing). This is also called opinion mining or attitude detection. In the text mining field, Sentiment Analysis is continuous area of research. It is a procedural treatment of attitude, feelings and textual content. The fundamental thought is to discover text polarity and order it as positive, negative, or neutral. It supports human to take a good judgment. This survey paper gives an extensive summary of the previous updates in this area. Several currently proposed algorithms and numerous upgrades to different SA applications have been investigated and summed up in this review. These articles are classified by their commitment to different SA techniques. Areas identified with SA (business monitoring, polarity observation, social media monitoring) that has recently attracted researchers is discussed. The fundamental objective of this survey is to provide a complete picture of SA practices and associated fields with brief explanation. The significant role of this study includes a refined classification of current papers and a depiction of ongoing patterns in sentiment analysis and research in its associated fields.