Abstract

Online peer support mental health forums provide an effective and accessible form of support, augmenting scarce clinical and face-to-face assistance. However, to enhance their effectiveness, it is essential to understand the unique characteristics of peer support user groups, and how they participate, contribute and communicate in these forums. This paper proposes and tests a novel approach that leverages stylometry analysis to uncover the unique characteristics of peer support user groups in such forums. Our approach identifies how each group empowers and supports other users, and what distinguishes them from others. The analysis shows that emotion-related words are crucial in identifying and distinguishing user groups based on their writing style. Comparative analysis of emotion expressions across user groups also uncovers the significance of emotional content in these forums in promoting mental well-being. Valued ‘senior contributors’ were more likely than all other groups including trained community guides to use a wide range of both positive and negative emotions in their posts. These findings have significant implications for improving the training of peer-mentors and moderators, scaling forum services, and improving guidelines for emotional expression among peer support users. Our approach presents an objective approach to differentiating the characteristics and communication patterns of valued senior contributors, mentors, and guides, enabling service providers to foster the kinds of communication that supports positive outcomes for distressed users.

Details

Title
Leveraging stylometry analysis to identify unique characteristics of peer support user groups in online mental health forums
Author
Kang, Yong-Bin 1 ; McCosker, Anthony 1 ; Farmer, Jane 2 

 Swinburne University of Technology, Australian Research Council (ARC) Centre of Excellence for Automated Decision-Making and Society (ADM+S), Hawthorn, Australia (GRID:grid.1027.4) (ISNI:0000 0004 0409 2862) 
 Swinburne University of Technology, Social Innovation Research Institute, Hawthorn, Australia (GRID:grid.1027.4) (ISNI:0000 0004 0409 2862) 
Pages
22979
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2906651335
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.