Sentiment analysis on streaming data using parallel computing

Abstract

Today as everything has become online and everyone has the chance to voice their opinion. Every opinion is important for the success of the company. Therefore, every company has started giving more and more important to this sentiment analysis, thereby making sentiment analysis a huge field in itself and a hot research topic in the field of natural language processing and linguistic communication. As more and more people are having access to the Internet, the Internet is filled with opinions about products, which has led to the data explosion and big data. And as we have to now do the analysis of this large amount of data, we have to find out some mechanism to make this process of analysis faster and more efficient. Parallel computing comes to the rescue in this case. Parallel computing has been a topic of research for a lot of years now. We can use this in the field of sentiment analysis as well. This is what is done in this work. The various ways in which sentiment analysis can be done using parallel computing are compared in terms of efficiency and time taken to compute. Streaming data has become the trend today as data is continuously being added to the Internet. So performing sentiment analysis on streaming data is much more helpful using parallel computing.