Spark-Based Sentiment Analysis of Tweets Using Machine Learning Algorithms

Abstract

Analysis of sentiment is an important aspect of machine learning and has found its vivid application in marketing and sales, political campaigns, etc. analysis of product reviews, company reviews have become an integral part of modern-day marketing, but it is difficult to process so many product reviews and ratings hence to cumulate all these we can use a neutral platform, social media. This paper addresses these problems of sentiment analysis of tweets; using machine learning techniques and big data analytics. We implement spark framework to achieve the map-reduced model. The result of the analysis shows that Support Vector Machine outperforms the other algorithms while considering both time consumption and accuracy