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From Perpetrators' Digital Footprints to Behavioral Communities: An Ontology-Driven Framework for Bengali Cyberbullying Analysis--- FULL VERSION — arXiv:2610.30885

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.30885
License (as archived): CC0-1.0
Archived: 2026-10-23T15:20:31.999Z
SHA-256 of the archived text: f8e9f829767c466301f07537ec0d9ddcc1c6da28a7b4e9dbe0c8e5a91e0cbdb9
Stable URL of this page: https://metraipolis.com/documento/dc_bf679242592c

How to cite

From Perpetrators' Digital Footprints to Behavioral Communities: An Ontology-Driven Framework for Bengali Cyberbullying Analysis--- FULL VERSION — arXiv:2610.30885 — arXiv (en), https://arxiv.org/abs/2610.30885 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_bf679242592c (Metraipolis archive dc_bf679242592c, sha256 f8e9f829767c466301f07537ec0d9ddcc1c6da28a7b4e9dbe0c8e5a91e0cbdb9)

BibTeX

@misc{dcbf679242592c,
  title = {From Perpetrators' Digital Footprints to Behavioral Communities: An Ontology-Driven Framework for Bengali Cyberbullying Analysis--- FULL VERSION — arXiv:2610.30885},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.30885},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_bf679242592c; sha256 f8e9f829767c466301f07537ec0d9ddcc1c6da28a7b4e9dbe0c8e5a91e0cbdb9},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.30885. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Cyberbullying involves behavioral and contextual patterns beyond isolated abusive messages. However, existing approaches remain fragmented across content detection, semantic representation, and network analysis, with limited interpretable perpetrator representations, multi-scale structural modeling, and explanations of behavior-driven similarity and influence propagation. These limitations hinder the identification of persistent perpetrators, characterization of behavioral communities, and assessment of potentially influential users. This paper proposes Ontology-Driven Cyberbullying Behavior and Network Analysis (ODCBNA), a perpetrator-centric framework integrating requirements-driven ontology design, knowledge graph construction, behavioral modeling, community analysis, and influence modeling. Using the Bengali Contextual and Diverse Cyberbullying (BenCoDiC) corpus as a use case, ODCBNA identifies $1{,}063$ users with at least three bullying comments or replies as perpetrators and represents each through a $64$-dimensional behavioral and contextual feature vector. Cosine similarity and $k$-nearest-neighbor modeling produce a weighted network with $27{,}554$ edges. Louvain analysis identifies six communities with a modularity of approximately $0.495$ and $27$ sub-communities. Feature-contribution analysis identifies the Video, Impact, and User Profile groups as the strongest contributors to behavioral similarity and community separation, while contextual dimensions support interpretation. Community-constrained influence analysis shows that IM Greedy achieves small positive gains in all six communities, although different seed-selection methods produce comparable diffusion spreads despite limited seed overlap. These findings provide an interpretable basis for understanding perpetrator behavior, community organization, and potential influence patterns in Bengali online environments.

Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv cs.CL, nuovi lavori del giorno).
Categorie arXiv: Computation and Language (cs.CL).
Pagina del lavoro: https://arxiv.org/abs/2610.30885 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-23T15:09:38.333Z dalla pagina https://arxiv.org/list/cs.CL/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).