A Comparative Study on Various Approaches of Sentimental Analysis

On social networking platforms, millions of people express their thoughts in the form of the text and images every day. A tweet or text present on the online social media networking sites is very useful to carry out the sentiments of the users about the products, news etc., but from these briefs and highly unstructured data sets generated with which great insights can be gained. Several organizations now use Twitter to inform the public about their services and products. An analysis is a method to evaluate the meaning of data, which is one of the fields of Natural Language Processing (NLP) and text data mining. The sentiment analysis of the unstructured data has many facets. This paper shows a comparative study of various methods and approaches to find out the sentiments from the unstructured data.