Sentiment Analysis (SA) is a computational treatment of opinions and emotions. And it is the most active area of Natural Language Processing (NLP), Social Network Mining and Multimedia Data mining. Sentiment analysis can be done for decision making process like product reviews, stock marketing, political debates, news articles and election results prediction. The developing significance of sentiment analysis with the popularity of social network such as Facebook, Twitter, Instagram and Flicker. The users of the social media express their feelings with both text and visual content. Predicting emotion from textual is easy but with visual content is quite difficult so far. A visual content does not contain any objects, locations and actions but it has cues about emotions, sentiment. Sentiment analysis of huge scale visual content can help better extract user sentiment towards topics and events such as image tweets, GIFs, videos. In this paper we analyze various research based on role of sentiment analysis on social media and come out with the evaluation and efficiency of sentiment analysis.