The advent of social media and the rapid development of mobile communication technologies have dramatically changed the way to express the feeling, attitude, mood, passion etc. People often express their reactions, fancies, preferences etc.Through social media in the form of short texts instead of long texts. In micro blogging services like twitter, people can share and discuss their views without any constraints. Thus, these are the sentiments of people which can characterize their behavior. Nowadays, politicians also refer facebook, twitter and blogs to collect reviews amongst the people about them. A model is developed which captures the comments of people and forwards it to the preprocessing module. It contains URL removal, stopword removal, tokenization, abbreviation expansion and stemming processes. Further the result obtained is passed on to neural network. Here, Recurrent Neural Network (RNN) model is used to predict the sentiments, whether audience have positive or negative responses. RNN uses its Long Short Term Memory (LSTM) module for processing of the data. The final result obtained is binary classification and representation of opinions. © 2018 IEEE.