User sentiment dynamics in social media: a comparative analysis of X and Threads

Rezki Khairunnas, Jeri Apriansyah Pagua, Ghina Fitriya, Yova Ruldeviyani

Research output: Contribution to journalArticlepeer-review

Abstract

This research examines the dynamics of user sentiment and its correlation with the usage factors of applications in the context of the competition between X (formerly Twitter) and Threads, a social media application under the umbrella of Meta. Through sentiment analysis of user reviews on the Google Play Store and App Store, the study aims to identify the key factors contributing to a significant decline in user engagement with Threads and the return of users to X. The method employed in this research is the support vector machine (SVM) for sentiment classification of reviews. The study then correlates the classified sentiments with application usage factors: usability, features, design, and support. The research findings indicate user sentiment influences user engagement, especially in features and design. The research concludes with insights regarding implications for application developers and suggests directions for future research.

Original languageEnglish
Pages (from-to)447-456
Number of pages10
JournalIAES International Journal of Artificial Intelligence
Volume14
Issue number1
DOIs
Publication statusPublished - Feb 2025

Keywords

  • Correlation
  • Sentiment analysis
  • Social media
  • Support vector machine
  • Threads
  • X (Twitter)

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