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 language | English |
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Pages (from-to) | 447-456 |
Number of pages | 10 |
Journal | IAES International Journal of Artificial Intelligence |
Volume | 14 |
Issue number | 1 |
DOIs | |
Publication status | Published - Feb 2025 |
Keywords
- Correlation
- Sentiment analysis
- Social media
- Support vector machine
- Threads
- X (Twitter)