Classification of Large Social Twitter Network Data Using R

Abstract

The development of social networks has altered computer science research. Now, a vast amount of data is available via Twitter, Facebook, emails, and IoT. (Internet of Things). So, storing and analyzing these data has become very difficult for academics. Conventional frameworks have been ineffective for processing massive amounts of data. R is an open-source programming language designed for large-scale data analysis with higher accuracy.
Additionally, it offers the chance to implement the R programming language. This essay examines the application of R to classify sizable social network data. The Naive Bayes method is used to categorize massive amounts of Twitter data. The experiment has demonstrated that a sizable portion of data may be adequately classified with positive outcomes utilizing the R framework.