Natural Language Processing Based Sentimental Analysis of Hindi (SAH) Script an Optimization Approach

Sentimental analysis is one of the most common applications of Natural Language Processing (NLP). Sentiment analysis, the term itself refers to identify the emotions and opinions of people through written text. It is concerned with information extraction from any text based on the polarity in social behavior whether it may be positive, negative or neutral. This paper presents a practical dynamic approach on to find the polarity of any sentence and analyse the opinion of the particular sentence. The proposed Sentimental Analysis of Hindi (SAH) script have adopted two different classifier Naïve Bayes Classifier and Decision Tree Classifier is used for the text extraction. The positive, neutral and negative result validation shows a comparative result of sentimental analysis.