Old crimes reported in new bottles
The disclosure of child sexual abuse on Twitter through the case #MeTooInceste
Bibliographic Data
| ID | 4697379 |
|---|---|
| Authors | Jesús C Aguerri (0000-0002-7730-8527, Universitat de Miguel Hernández d'Elx, corresponding author), L Molnar (0000-0001-8692-9256, University of Lausanne), Fernando Miró-Llinares (0000-0001-6379-5857, Universitat de Miguel Hernández d'Elx) |
| Year | 2023 |
| Volume | 13 |
| Issue | 1 |
| Publication date | 2023-02-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-023-01029-4 |
| OpenAlex | W4318832645 |
| Language | EN |
| Citations received | 5 |
| References cited | 61 |
Movements such as #MeToo have shown how an online trend can become the vehicle for collectively sharing personal experiences of sexual victimisation that often remains unreported to the criminal justice system. These social media trends offer new opportunities to social scientists who investigate complex phenomena that, despite existing since time immemorial, are still taboo and difficult to access. They also bring technical difficulties, as the challenge to identify reports of victimisation, and new questions about the characteristic of the events, the role that victimisation testimonies play and the capacity to detect them by analysing their characteristics. To address these issues, we collected 91,501 tweets under the hashtag #MeTooInceste, posted from the 20 to 27 January 2021. A model was fitted using Latent Dirichlet Allocation that detected 1688 tweets disclosing experiences of child sexual abuse, with an accuracy of 91.3% [± 3%] and a recall of 93.1% [± 5%]. We performed Conjunctive Analysis of Case Configurations on the tweets identified as disclosures of victimisation and found that long tweets posted by users with small accounts, without URL or picture, were more likely to be related to disclosure of child sexual abuse. We discuss the possibilities of these trends and techniques offer for research and practice
Child sexual abuse · Criminology · Internet privacy · Poison control · Political science · Sexual abuse · Social media · Suicide prevention · Taboo · Victimisation · World Wide Web · Computer Science · Crime, Deviance, and Social Control · Hate Speech and Cyberbullying Detection · Law · Medicine · Misinformation and Its Impacts · Psychology
Incest
Finding scientific topics
Tidytext
The prevalence of child sexual abuse in community and student samples
Hashtag activism and message frames among social movement organizations
Rtweet
Using typologies of victimization worry to create strategies for reducing fear of crime
European Sourcebook of Crime and Criminal Justice Statistics – 2021
The diffusion of misinformation on social media
Facilitators and Barriers to Child Sexual Abuse (CSA) Disclosures
“I Still Feel Like I Am Not Normal”
Adult Disclosure of Child Sexual Abuse
When Did I Become a Victim? Exploring Narratives of Male Childhood Sexual Abuse
Trends in U.S. Adolescents’ media use, 1976–2016
What are we ‘tweeting’ about obesity? Mapping tweets with topic modeling and Geographic Information System
The virtual sphere
Virtual Criminality
Theory-Driven Analysis of Large Corpora
MeToo as a Connective Movement
Whose Opinion Matters? Analyzing Relationships Between Bitcoin Prices and User Groups in Online Community
Sharing #MeToo on Twitter
Stigmatization of People with Pedophilia
Participant' Perceptions of Twitter Research Ethics
Hunter or Prey? Exploring the Situational Profiles that Define Repeated Online Harassment Victims and Offenders
| Unique citing works | 5 |
|---|---|
| Citations per year | 2,5 |
| Citation span | 2024 - 2025 (2) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 5 |