Toward Integrated Solutions: A Systematic Interdisciplinary Review of Cybergrooming Research

Authors: Heajun An, Marcos Silva, Qi Zhang, Arav Singh, Minqian Liu, Xinyi Zhang, Sarvech Qadir, Sang Won Lee, Lifu Huang, Pamela J. Wisniewski, Jin-Hee Cho
Published: 2025-02-18 | Updated: 2025-07-31

Source: https://arxiv.org/abs/2503.05727

PDF: https://arxiv.org/pdf/2503.05727

AIにより推定されたラベル

敵対的学習 サイバーグルーミング研究 文献レビュー方法論

※ こちらのラベルはAIによって自動的に追加されました。そのため、正確でないことがあります。
詳細は文献データベースについてをご覧ください。

Abstract

Cybergrooming exploits minors through online trust-building, yet research remains fragmented, limiting holistic prevention. Social sciences focus on behavioral insights, while computational methods emphasize detection, but their integration remains insufficient. This review systematically synthesizes both fields using the PRISMA framework to enhance clarity, reproducibility, and cross-disciplinary collaboration. Findings show that qualitative methods offer deep insights but are resource-intensive, machine learning models depend on data quality, and standard metrics struggle with imbalance and cultural nuances. By bridging these gaps, this review advances interdisciplinary cybergrooming research, guiding future efforts toward more effective prevention and detection strategies.