Classification of Large Social Twitter Network Data Using R

Authors

  • Muhammad Umer COMSATS University Islamabad Sahiwal Campus
  • Muhammad Javaid Iqbal COMSATS University Islamabad, Lahore Campus
  • Tuba Mansoor Riphah International University
  • Usman Nasir COMSATS University Islamabad, Sahiwal Campus
  • Ali Asif University of Okara, Pakistan
  • Atif Ikram Faculty of Ocean Engineering Technology and Informatics, University Malaysia Terengganu

DOI:

https://doi.org/10.56536/jicet.v3i1.56

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 in 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.

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Published

2023-03-02