Identifying Symbolic Modeling of Grooming Precursors in Social Media

Short-form video platforms such as TikTok and Instagram Reels increasingly circulate dating and lifestyle advice that may normalize coercive relational scripts, framing jealousy as devotion or secrecy as intimacy. A key challenge for preventing technology-facilitated child sexual exploitation is that early grooming precursors can be communicated through audiovisual choices, such as tone, pacing, setting, and editing, that make manipulative narratives appear benign. This qualitative multimedia content analysis identified recurring observable patterns of symbolic modeling through which relational and boundary-shaping cues associated with early-stage sexualized grooming are framed as ordinary dating or lifestyle advice in public TikTok and Instagram posts. Guided by Bandura’s social cognitive theory of mass communication, a purposive sample of 100 archival posts (50 per platform) was coded in MAXQDA using a structured multimodal observation protocol. Beyond its findings, the study contributes a transferable protocol for coding relational risk across visual, audio, and on-screen text channels simultaneously, extending grooming-detection methods beyond their text-only focus. Analysis produced a taxonomy of 10 recurring masking categories, derived from 289 operationally defined codes and interpreted through four themes. Masking operated primarily through presentation-layer conventions: simulated closeness, ordinary platform packaging, staged intimacy, and instructional framing dominated the corpus. Explicit grooming-literature cues were rare, appearing in 19 of 100 posts, and two cues, secrecy normalization and isolation, never appeared. Findings may inform prevention education and support future multimodal detection research.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-23
DOI
https://doi.org/10.5281/zenodo.21513869
Primary Topic
Sex work and related issues
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Identifying Symbolic Modeling of Grooming Precursors in Social Media

H.N. Landress
Zenodo (CERN European Organization for Nuclear Research)
Sex work and related issues
preprint

Identifying Symbolic Modeling of Grooming Precursors in Social Media

H.N. Landress
preprint en

Abstract

Short-form video platforms such as TikTok and Instagram Reels increasingly circulate dating and lifestyle advice that may normalize coercive relational scripts, framing jealousy as devotion or secrecy as intimacy. A key challenge for preventing technology-facilitated child sexual exploitation is that early grooming precursors can be communicated through audiovisual choices, such as tone, pacing, setting, and editing, that make manipulative narratives appear benign. This qualitative multimedia content analysis identified recurring observable patterns of symbolic modeling through which relational and boundary-shaping cues associated with early-stage sexualized grooming are framed as ordinary dating or lifestyle advice in public TikTok and Instagram posts. Guided by Bandura’s social cognitive theory of mass communication, a purposive sample of 100 archival posts (50 per platform) was coded in MAXQDA using a structured multimodal observation protocol. Beyond its findings, the study contributes a transferable protocol for coding relational risk across visual, audio, and on-screen text channels simultaneously, extending grooming-detection methods beyond their text-only focus. Analysis produced a taxonomy of 10 recurring masking categories, derived from 289 operationally defined codes and interpreted through four themes. Masking operated primarily through presentation-layer conventions: simulated closeness, ordinary platform packaging, staged intimacy, and instructional framing dominated the corpus. Explicit grooming-literature cues were rare, appearing in 19 of 100 posts, and two cues, secrecy normalization and isolation, never appeared. Findings may inform prevention education and support future multimodal detection research.

Zenodo (CERN European Organization for Nuclear Research)
Gender equality
Sex work and related issues
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.