Efficient time series sentiment analysis of user generated data using deep learning

Abstract

In this world, there has always been some dilemma while purchasing any product. People usually tend to spend a lot of time in deciding the intricacies of daily activities ranging from which eatery to dine at to which movie to go for . Earlier, asking known associates, i.e., word of mouth was the main source of information. Of late, with the world going online, this has been hugely replaced by online reviews. These reviews represent the general opinion on the corresponding products, person or events. Naturally, to improve business decision, meaningful information must be obtained after processing these reviews. In order to mine the opinion, the inherent sentiment needs to be analyzed. Thus, extracting the concealed sentiments from user reviews has become a vital task. The most obvious approach to extract the pertinent knowledge is classification of the sentiment associated with the opinion. Conti... newline