A Bi-GRU with attention and CapsNet hybrid model for cyberbullying detection on social media
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
The gated Recurrent Units with Attention (GRU-Att) model has demonstrated exciting results in detecting bullying behavior in social media text.
“The gated Recurrent Units with Attention (GRU-Att) model has also demonstrated exciting results in detecting bullying behavior in a social media text.”
From A Review on Deep-Learning-Based Cyberbullying Detection (2023) · cites this paper as [71]
GRU-Att can capture long-term dependencies in sequential data faster than the LSTM model while capturing the important part of the input text.
“The model can capture long-term dependencies in sequential data faster than the LSTM model while capturing the important part of the input text by combining Gated Recurrent Units (GRUs) with attention mechanisms.”
From A Review on Deep-Learning-Based Cyberbullying Detection (2023) · cites this paper as [71]
GRU-Att can more accurately interpret and categorize the behavior of cyberbullying on social media platforms.
“This makes it possible for the model to more accurately interpret and categorize the behavior of cyberbullying on social media platforms [71,123,124].”
From A Review on Deep-Learning-Based Cyberbullying Detection (2023) · cites this paper as [71]
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References 41 · Cited by 87
- Authors
- Kumar, A., & Sachdeva, N.
- Affiliations
- Delhi Technological University (IN)
- Corresponding author
- Kumar, Akshi
- ORCID
- Kumar, Akshi
- Venue
- World Wide Web
- Published
- 2021-07-22
- Volume
- 25
- Issue
- 4
- Pages
- 1537-1550
- ISSN
- 1386-145X (ISSN-L)
- 1573-1413
- OpenAlex
- W3186804201
- Cited by
- 87
- References
- 41
- Citations by year
- 2026: 6 · 2025: 23 · 2024: 18 · 2023: 25 · 2022: 14 · 2021: 1
- FWCI
- 5.13
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- World Wide Web (publishedVersion)
- e-space (Manchester Metropolitan University) (acceptedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Keywords
- cyberbullying detection, social media text, BiGRU, self-attention, capsule networks, hybrid deep learning model, online harassment, text classification
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