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SINTA 1
User sentiment dynamics in social media: a comparative analysis of X and Threads
IAES International Journal of Artificial Intelligence
ISSN 2252-8938, 2089-4872
Terbit 2025-02-01
Penerbit Institute of Advanced Engineering and Science
Bahasa eng
Abstrak
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.
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Sumber metadata: OAI-PMH (metadata jurnal) http://ijai.iaescore.com/index.php/IJAI/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc)
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<dc:title xml:lang="en-US">User sentiment dynamics in social media: a comparative analysis of X and Threads</dc:title>
<dc:creator>Khairunnas, Rezki</dc:creator>
<dc:creator>Pagua, Jeri Apriansyah</dc:creator>
<dc:creator>Fitriya, Ghina</dc:creator>
<dc:creator>Ruldeviyani, Yova</dc:creator>
<dc:subject xml:lang="en-US"></dc:subject>
<dc:subject xml:lang="en-US">Correlation; Sentiment analysis; Social media; Support vector machine; Threads X (Twitter)</dc:subject>
<dc:description xml:lang="en-US">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.</dc:description>
<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
<dc:contributor xml:lang="en-US">Ministry of Communication and Information Technology (Kominfo), Indonesia</dc:contributor>
<dc:date>2025-02-01</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
<dc:type xml:lang="en-US"></dc:type>
<dc:format>application/pdf</dc:format>
<dc:identifier>https://ijai.iaescore.com/index.php/IJAI/article/view/25272</dc:identifier>
<dc:identifier>10.11591/ijai.v14.i1.pp447-456</dc:identifier>
<dc:source xml:lang="en-US">IAES International Journal of Artificial Intelligence (IJ-AI); Vol 14, No 1: February 2025; 447-456</dc:source>
<dc:source>2252-8938</dc:source>
<dc:source>2089-4872</dc:source>
<dc:source>10.11591/ijai.v14.i1</dc:source>
<dc:language>eng</dc:language>
<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/view/25272/14386</dc:relation>
<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/downloadSuppFile/25272/3556</dc:relation>
<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/downloadSuppFile/25272/3557</dc:relation>
<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/downloadSuppFile/25272/3559</dc:relation>
<dc:rights xml:lang="en-US">Copyright (c) 2024 Institute of Advanced Engineering and Science</dc:rights>
<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>
Sitasi dan pengindeksan
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Sitasi artikel ini
APA 7
Khairunnas, R., Pagua, J. A., Fitriya, G., & Ruldeviyani, Y. (2025). User sentiment dynamics in social media: a comparative analysis of X and Threads. IAES International Journal of Artificial Intelligence, 14(1), 447–456. https://doi.org/10.11591/ijai.v14.i1.pp447-456
Salin
IEEE
R. Khairunnas, J. A. Pagua, G. Fitriya, and Y. Ruldeviyani, “User sentiment dynamics in social media: a comparative analysis of X and Threads,” IAES International Journal of Artificial Intelligence, vol. 14, no. 1, pp. 447–456, 2025, doi: 10.11591/ijai.v14.i1.pp447-456.
Salin
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