Techniques of Sentiment Classification, Emotion Detection, Feature Extraction and Sentiment Analysis: A Comprehensive Review - Mamatha, M; Thriveni, J; Venugopal, KR (International Journal of Computer Sciences and Engineering, 2025)
Sentiment Analysis(SA) is a way of analyzing the sentiment/emotion in the sentence. Entity, sentence or document- level sentences have been carried out to discover the polarity of text. Sentiment is measured using various approaches such as lexical-based and supervised machine learning methods. This survey focuses on various methods for Feature Extraction and Emotion Detection. Before applying any algorithm for sentiment polarity identification, preprocessing is to be carried over. Machine learning(ML) techniques such as Naive Bayes, SVM, and Max Entropy have been applied to identify the polarity score that are classified as positive, negative or neutral. Feature Selection method identifies a subset of most functional features from the entire set of features. The major challenge in Opinion mining lies in identifying the emotion expressed in the text. This survey provides an insight into the efficient techniques, methods and future scope in opinion mining investigation.