Descriptive Analysis of Sentiment Analysis in...

Descriptive Analysis of Sentiment Analysis in Big Data Social Streams

Author Name : Raghavendra M, Dr. Prathima G, Dr. Revathi V

ABSTRACT Rapid improvement of internet, users express their feelings and views on internet. With the rapid development of social media, different users share valuable location on changing reviews, ideas on different services. Opinion mining is the growing area, which describes different user’s feedback about any concept, relates to social media applications from big data sources. Sentiment analysis (SA) is an application of Natural Language Processing (NLP) has been witnessed of blooming interest over past years. Generally sentiment/opinion be the classifying the basic representation of text positive, negative and neutral expressions of different users. Traditionally different calculation methods/approaches/algorithms available for mining opinion of different users in social networks. Before applying any algorithm to explore opinion mining there are basic steps available i.e. pre-processing, polarity detection is carried out sentiment over document level, sentiment level like different granularities. This paper describes about different calculations and evaluation of social related sentiment analysis challenges discussed in real time fields.