Novel idea
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Harnessing the Power of Interdisciplinary Research with Psychology-Informed Cyberbullying Detection Models
– MUST READ! -
A Human-Centered Systematic Literature Review of Cyberbullying Detection Algorithms
– section 2 is good -
Extending the Current Theorization on Cyberbullying: Importance of Including Socio-Psychological Perspectives
– learn socio-psy! -
Unsupervised cyberbullying detection via time-informed Gaussian mixture model
– energy based and threshold -
Unsupervised cyber bullying detection in social networks
– SOM (a clustering) -
Automatic cyberbullying detection: A systematic review
– a good review paper -
A Detailed Survey On Cyberbullying in Social Networks
– a fine supp -
Predicting Cyberbullying on Social Media in the Big Data Era Using Machine Learning Algorithms: Review of Literature and Open Challenges | IEEE Journals & Magazine | IEEE Xplore
– a fine supp -
Current limitations in cyberbullying detection: On evaluation criteria, reproducibility, and data scarcity
– a fine supp
Technical
- SIGIR Hate speech detection is not as easy as you may think: A closer look at model validation
- WSDM 19 Xbully: Cyberbullying detection within a multi-modal context
- SDM 19 Hierarchical attention networks for cyberbullying detection on the instagram social network (# 50)
- WWW 20 Temporal properties of cyberbullying on instagram
- IJCAI 19 PI-bully: Personalized cyberbullying detection with peer influence
- WWW 19 Robust cyberbullying detection with causal interpretation
- Session-based cyberbullying detection: Problems and challenges
- A comparative analysis of machine learning techniques for cyberbullying detection on twitter
- BullyBlocker: toward an interdisciplinary approach to identify cyberbullying
- See no evil, hear no evil: Audio-visual-textual cyberbullying detection
- Cyberbullying detection using probabilistic socio-textual information fusion
- Modeling Temporal Patterns of Cyberbullying Detection with Hierarchical Attention Networks
- BullyNet: Unmasking Cyberbullies on Social Networks
- Socially responsible ai algorithms: Issues, purposes, and challenges
- Mitigating bias in session-based cyberbullying detection: A non-compromising approach
- Improving Cyberbullying Detection with User Interaction
- Weakly supervised cyberbullying detection using co-trained ensembles of embedding models
- Multi-modal cyberbullying detection on social networks
- Detection and Prevention of Cyberbullying on Social Media
- Cyberbullying detection with birnn and attention mechanism
- Detecting early signs of cyberbullying in social media
- Toward multimodal cyberbullying detection
- Mining patterns of cyberbullying on twitter
- Optimal online cyberbullying detection
- Cyberbullying detection on instagram with optimal online feature selection
- Aggressive, repetitive, intentional, visible, and imbalanced: Refining representations for cyberbullying classification
- Weakly supervised cyberbullying detection with participant-vocabulary consistency
- A multi-platform dataset for detecting cyberbullying in social media
- Fairness across network positions in cyberbullying detection algorithms
- Review of Machine Learning methods for Identification of Cyberbullying in Social Media
- Time reveals all wounds: Modeling temporal characteristics of cyberbullying
Related topics
- Humour and (mock) aggression: Distinguishing cyberbullying from roasting - ScienceDirect
- Comprehensive review of cybercrime detection techniques
- CyberAid: Are your children safe from cyberbullying? - ScienceDirect
- Cyberbullying and mental health in adults: the moderating role of social media use and gender
- Cyberbullying and Cyberstalking on Online Social Networks
- Towards Cyberbullying-free social media in smart cities: a unified multi-modal approach
- Deephate: Hate speech detection via multi-faceted text representations
- On the dynamics of political discussions on Instagram: A network perspective
- Causal Learning for Socially Responsible AI