Big Data Sentiment Analysis of Twitter Data

Abstract

The term "big data" is becoming increasingly common these days. The amount of data generated is directly proportional to the amount of time spent on social media each day. The majority of users consider Twitter to be one of the most popular social networking platforms. The rise of social media has sparked an incredible amount of curiosity among those who use the internet nowadays. The information collected from these social networking sites may be put to a variety of uses, including forecasting, marketing, and the study of user sentiment. Twitter is a social media platform that is commonly used for making remarks in the form of brief status updates. A sentiment analysis may be performed on some or all of the millions of tweets that are received each year. Managing such a massive volume of unstructured data, on the other hand, is a laborious effort to do. To effectively manage large amounts of data, the analytics tools and models that are now on the market are insufficiently equipped and positioned. For this reason, it is essential to make use of a cloud storage solution for the applications of this kind. As a result, we have used Hadoop for the intelligent analysis as well as the storing of large amounts of data. In this article, we offer a system that does sentiment analysis on tweets using the Cloud.

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