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Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

Resilience in Web-Based Mental Health Communities: Building a Resilience Dictionary With Semiautomatic Text Analysis.

Yong-Bin Kang¹, Anthony McCosker^1,2, Peter Kamstra²

¹Australian Research Council (ARC) Centre of Excellence for Automated Decision-Making and Society (ADM+S), Swinburne University of Technology, Victoria, Australia.

JMIR Formative Research

|September 22, 2022

Summary

This study developed a resilience dictionary for online mental health forums, identifying key indicators like social capital and belonging that foster resilience. This resource aids in optimizing support and moderation for improved user outcomes.

Keywords:

content moderation mental health peer-support forum resilience dictionary text analysis topic modeling

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Area of Science:

Digital mental health
Online peer support
Resilience research

Background:

Resilience is crucial for mental health, informing personal and community prevention strategies.
Online peer-support forums enhance resilience by facilitating shared experiences and support.
Limited research exists on how resilience is realized in these digital spaces.

Purpose of the Study:

To develop a resilience dictionary for online mental health peer-support forums.
To characterize resilience indicators and their realization within these forums.
To guide analysis and improve resilience outcomes through targeted moderation.

Main Methods:

A semiautomatic approach combining topic modeling and qualitative content analysis.
A 4-phase pipeline: preprocessing, theme discovery, indicator conceptualization, and dictionary generation.
Analysis of 70,179 posts from SANE Australia forum (2018-2020).

Main Results:

A resilience dictionary and taxonomy were created, detailing indicators like social capital, belonging, learning, adaptive capacity, and self-efficacy.
Common themes and descriptive terms associated with resilience indicators were identified.
Learning, belonging, and social capital were frequently realized, with belonging and learning foundational to others.

Conclusions:

The developed resilience dictionary enhances understanding of resilience in web-based mental health forums.
Provides guidance for improving training and automated moderation systems.
Facilitates better support and enhanced resilience outcomes in online mental health communities.