Continuous Tweet Stream Analysis using Apache Spark Streaming API and Kafka

Social media has become a trend nowadays people are spending more time in social media platform like Facebook, Twitter, Instagram to share their opinions, creating new interests, ideas and generate awareness. These provide a major platform for collecting information which helps us to analyze them for our needs. One such microblogging social network is twitter which allows information collaboration and quick information sharing that provides relief from rising emails. Twitter has several millions of people tweeting and expressing their perspectives on a due to its distinctively brief and straightforward expressing technique. This enormous volume of raw data from tweets can be utilised for analysis and processing based on industrial or business needs. In this technical paper, the application of tweet sentiment analysis by extracting a vast number of tweets using continuous tweet stream provided by Spark and Kafka has been done. This system fetches live tweets from Twitter based on the search criteria, process the tweets, by using text mining techniques and classify them based on different labels.