Heterogeneous Graph Neural Network Framework for Session-Based Cyberbullying Detection
Cyberbullying is one of the harmful activities on social networks that particularly affects the mental well-being of adolescents. Recent research has focused on session-based approaches to cyberbullying detection, which consider various components of a social media session, including posts, comments...
Saved in:
Main Authors: | Munkhbuyan Buyankhishig, Thanda Shwe, Israel Mendonca, Masayoshi Aritsugi |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/11052219/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Talking Wikidata: Communication Patterns and Their Impact on Community Engagement in Collaborative Knowledge Graphs
by: Koutsiana, Elisavet, et al.
Published: (2025-04-01) -
Sylph: An Unsupervised APT Detection System Based on the Provenance Graph
by: Kaida Jiang, et al.
Published: (2025-07-01) -
Anomaly detection in graph databases using graph neural networks: Identifying unusual patterns in graphs
by: Ismail Chetoui, et al.
Published: (2025-09-01) -
The hybrid sequential recommender system synthesis method based on attention mechanism with automatic knowledge graph construction
by: Дмитро Андросов, et al.
Published: (2025-03-01) -
Large Language Models for Knowledge Graph Embedding: A Survey
by: Bingchen Liu, et al.
Published: (2025-07-01)