Advancement Through Research
Sentiment analysis (SA) is an enduring area for research especially in the field of text analysis. SA is the way of computationally handling the opinions, expressions and feelings towards the subject/object of the text. This survey article provides a summary of the important progress in the field of sentiment analysis. Numerous recent enhancements of machine learning algorithms, their accuracy as well as their applications are briefly presented in the article. The application fields of SA (sensitivity detection, resource building and transfer learning), the recent trends for research are also discussed. This study mainly presents a complete picture of machine learning techniques mainly categorized as classification and clustering techniques, use for SA strategies and the related fields with brief subtleties. The main motive of this paper is to incorporate the categorization of articles and illustrations of the ongoing researches in the field of sentiment analysis and its applications.
Clustering Techniques, Classification Techniques, Machine Learning, Maximum Entropy, Naïve Bayes (NB), Natural Language Processing (NLP), Part of Speech (POS), Sentiment analysis (SA), Support Vector Machine (SVM)
