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Engineering Proceedings
Volume 141
Issue 1
10.3390/engproc2026141013
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Proceeding Paper

Sentiment Analysis of X Users in Digital Art: Comparison Between Algorithms †

by
Riana Magdalena Silitonga
1,*,
Vivi Triyanti
1,
Feliks Prasepta Sejahtera Surbakti
1,
Devi Angrahini Anni Lembana
2,
Valencia Catheryn Wilianto
1,*,
Jennifer Angel Gala
1,
Kayleen Gabreila
1 and
Indah Munica Sari
1
1
Department of Industrial Engineering, Atma Jaya Catholic University of Indonesia, Sampora, Tangerang Selatan 15345, Indonesia
2
Department of Management, Atma Jaya Catholic University of Indonesia, Jakarta 12930, Indonesia
*
Authors to whom correspondence should be addressed.
†
Presented at the 9th Eurasian Conference on Educational Innovation 2026 (ECEI 2026), Da Nang City, Vietnam, 30 January–2 February 2026.
Eng. Proc. 2026, 141(1), 13; https://doi.org/10.3390/engproc2026141013
Published: 9 June 2026
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Abstract

The rapid development of AI Technology has significantly influenced digital art and triggered widespread discussion on social media platforms, particularly X. The use of AI in generating visual artworks and digital content has elicited diverse public responses, ranging from support for technological innovation to concerns regarding originality and the role of human artists. In this study, a total of 1737 tweets were collected through a data crawling process using relevant keywords and processed using RapidMiner through preprocessing stages to analyze user sentiment on the X platform toward the application of AI in digital art. The data include data cleaning, text normalization, and tokenization, before being classified into positive and negative sentiments. Three classification algorithms, Naïve Bayes, support vector machine (SVM), and decision tree, were applied to compare sentiment distributions. The results show that the Naïve Bayes model classified 30.5% of tweets as positive and 69.5% as negative, while the SVM and Decision Tree models showed a stronger bias toward negative sentiment, with 93.3% and 88.8% negative classifications, respectively. These findings indicate that negative sentiment toward AI in digital art is more dominant among users.
Keywords: AI; digital art; decision tree; Naïve Bayes; support vector machine (SVM); sentiment analysis AI; digital art; decision tree; Naïve Bayes; support vector machine (SVM); sentiment analysis

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MDPI and ACS Style

Silitonga, R.M.; Triyanti, V.; Surbakti, F.P.S.; Lembana, D.A.A.; Wilianto, V.C.; Gala, J.A.; Gabreila, K.; Sari, I.M. Sentiment Analysis of X Users in Digital Art: Comparison Between Algorithms. Eng. Proc. 2026, 141, 13. https://doi.org/10.3390/engproc2026141013

AMA Style

Silitonga RM, Triyanti V, Surbakti FPS, Lembana DAA, Wilianto VC, Gala JA, Gabreila K, Sari IM. Sentiment Analysis of X Users in Digital Art: Comparison Between Algorithms. Engineering Proceedings. 2026; 141(1):13. https://doi.org/10.3390/engproc2026141013

Chicago/Turabian Style

Silitonga, Riana Magdalena, Vivi Triyanti, Feliks Prasepta Sejahtera Surbakti, Devi Angrahini Anni Lembana, Valencia Catheryn Wilianto, Jennifer Angel Gala, Kayleen Gabreila, and Indah Munica Sari. 2026. "Sentiment Analysis of X Users in Digital Art: Comparison Between Algorithms" Engineering Proceedings 141, no. 1: 13. https://doi.org/10.3390/engproc2026141013

APA Style

Silitonga, R. M., Triyanti, V., Surbakti, F. P. S., Lembana, D. A. A., Wilianto, V. C., Gala, J. A., Gabreila, K., & Sari, I. M. (2026). Sentiment Analysis of X Users in Digital Art: Comparison Between Algorithms. Engineering Proceedings, 141(1), 13. https://doi.org/10.3390/engproc2026141013

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