A Survey of Approaches for Sentiment Analysis on Social Media

Social network is attaining significant attention in present world. By using these social network platforms such as face book, instagram, twitter through the internet facility, it is becoming our day to day life and more economical as well as very fast access data platform to all of us. However due to the massive data available on social media, there are many issues characterized such as size of the data, noise in the data and many more. Because of these issues data of social media platform becomes complex for analysis or getting the useful information. Anyway there are numerous methodologies accessible for some internet based life stage, for example, Facebook, Instagram, Tumbler and so on, so we can break down these information by utilizing Python, R and a lot more dialects of information investigation. We can recover, break down and decipher this informal community information for research reason or to settle on any future choice. With a huge number of discussions occurring on interpersonal organizations consistently they offer a rich information source that can be gotten to in a relatively easy manner. This paper gives a brief discussion about the approaches of sentiment analysis in which we elaborate about different types of methods in order to perform sentiment analysis on data sets, which is basically related to the twitter data.