Analyzing Cyberbullying Negative Content on Twitter Social Media with the RoBERTa Method
Open accessAbstract
Social media is an online-based communication tool that can make it easier for users to interact among fellow users without any area and time restrictions. Indonesia has the highest number of social media users in the world. The Twitter social media platform is a place where users can pour out their whole hearts in the form of tweets. Free and diverse interactions on Twitter have a considerable influence on the psychological condition of its users. Cyberbullying or online bullying is an act of humiliating or hurting other people's feelings intentionally and repeatedly on social media, messages, or in other ways. In this study, the RoBERTa classification method was used to detect cyberbullying tweets with a best accuracy score of 86.9% and an f1-score of 77.5%.
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Yani et al. used RoBERTa to detect cyberbullying on Twitter and obtained an accuracy score of 86.9% and an F1 score of 77.5%.
“Yani et al. [49] utilized RoBERTa to detect cyberbullying on the popular social media platform Twitter. After experimental analysis, they obtained an accuracy score of 86.9% and an F1 score of 77.5%.”
From A Review on Deep-Learning-Based Cyberbullying Detection (2023) · cites this paper as [49]
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Cites
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Impact of Tokenization on Language Models: An Analysis for Turkish
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Flagged first, then by citations
Research works printed but not linked: 3
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Sorted by citations
A Review on Deep-Learning-Based Cyberbullying Detection
Hasan, M. T., Hossain, M. A. E., Mukta, M. S. H., Akter, A., Ahmed, M., & Islam, S. (2023) · Future Internet · doi:10.3390/fi15050179 · Cited by 103 · see citing works
“Yani et al. [49] utilized RoBERTa to detect cyberbullying on the popular social media platform Twitter.”
Background
- Authors
- Yani, M. A. A., & Maharani, W.
- Affiliations
- Telkom University (ID)
- ORCID
- Maharani, Warih
- Venue
- JINAV: Journal of Information and Visualization
- Publisher
- Yayasan Ahmar Cendekia Indonesia
- Published
- 2023-02-02
- Volume
- 4
- Issue
- 1
- Pages
- 61-69
- ISSN
- 2746-1440 (ISSN-L)
- OpenAlex
- W4385832096
- Cited by
- 6
- References
- 8
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2023: 2
- FWCI
- 0.53
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- JINAV Journal of Information and Visualization (publishedVersion, cc-by-nc-sa)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Physical Sciences › Computer Science › Artificial Intelligence › Text and Document Classification Technologies
- Keywords
- cyberbullying detection, Twitter, RoBERTa, text classification, negative sentiment, cyberbullying, Indonesian tweets
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