Finding Understanding and Support: Navigating Online Communities to Share and Connect at the intersection of Abuse and Foster Care Experiences

TL;DR

The paper investigates trauma-focused online discourse at the intersection of foster care and abuse-survivor communities on Reddit using a decade of data and mixed methods. It combines BERTopic-based topic modeling, qualitative coding, classifiers for cross-boundary posts, and propensity score matching to characterize boundary-crossing users and their discourse. The findings show boundary-crossers, though few, are central, adopting multiple social roles and receiving more engagement, suggesting they act as connectors or boundary spanners across communities. The authors propose trauma-informed design interventions—algorithmic guidance to related communities, badges for cross-posters, and moderator-augmented collaboration—to support survivors and improve information access and peer support in these sensitive online ecosystems.

Abstract

Many children in foster care experience trauma that is rooted in unstable family relationships. Other members of the foster care system like foster parents and social workers face secondary trauma. Drawing on 10 years of Reddit data, we used a mixed methods approach to analyze how different members of the foster care system find support and similar experiences at the intersection of two Reddit communities - foster care, and abuse. Users who cross this boundary focus on trauma experiences specific to different roles in foster care. While representing a small number of users, boundary crossing users contribute heavily to both communities, and, compared to matching users, receive higher scores and more replies. We explore the roles boundary crossing users have both in the online community and in the context of foster care. Finally, we present design recommendations that would support trauma survivors find communities more suited to their personal experiences.

Figures (2)

• Figure 1: This Figure shows how we built a topic model, qualitatively analyzed topics, and then used the topics for a classifier. One classifier predicted topics discussed by boundary crossing users in the foster care community and the second predicted topics discussed by boundary crossing users in the abuse community. Finally, we used axial coding of cross-posting predictive topics to describe discourse at the intersection of the two communities.
• Figure 2: This figure shows the distribution of propensity logits for boundary crossing and matching users