Author
Listed:
- Virginia Morini
(Department of Computer Science, University of Pisa, 56127 Pisa, Italy
Institute of Information Science and Technologies “A. Faedo” (ISTI), National Research Council (CNR), 56124 Pisa, Italy
These authors contributed equally to this work.)
- Salvatore Citraro
(Institute of Information Science and Technologies “A. Faedo” (ISTI), National Research Council (CNR), 56124 Pisa, Italy
These authors contributed equally to this work.)
- Elena Sajno
(Humane Technology Lab, Catholic University of the Sacred Heart, 20123 Milan, Italy
Department of Computer Science, Università degli Studi di Milano, 20133 Milan, Italy
These authors contributed equally to this work.)
- Maria Sansoni
(Humane Technology Lab, Catholic University of the Sacred Heart, 20123 Milan, Italy
Department of Psychology, Catholic University of the Sacred Heart, 20123 Milan, Italy
These authors contributed equally to this work.)
- Giuseppe Riva
(Humane Technology Lab, Catholic University of the Sacred Heart, 20123 Milan, Italy
Applied Technology for Neuro-Psychology Lab, IRCCS Istituto Auxologico Italiano, 20145 Milan, Italy)
- Massimo Stella
(CogNosco Lab, Department of Psychology and Cognitive Science, University of Trento, 38068 Rovereto, Italy
These authors contributed equally to this work.)
- Giulio Rossetti
(Institute of Information Science and Technologies “A. Faedo” (ISTI), National Research Council (CNR), 56124 Pisa, Italy
These authors contributed equally to this work.)
Abstract
Online social platforms increasingly function as informal self-help environments for individuals experiencing depression, offering spaces for emotional expression and peer support outside traditional clinical settings. However, how coping strategies and psychological engagement states—individuals’ emotional and cognitive involvement in managing their condition—are reflected through online self-disclosure remains poorly understood. We analyzed a large-scale dataset from Reddit depression-related communities to investigate how different psycho-linguistic profiles and coping orientations emerge from users’ language. We collected posts and comments from over 300,000 users across six depression-focused subreddits over two years. User-generated text was characterized through multiple psychological and linguistic dimensions capturing emotions, sentiment, subjectivity, and related features, then aggregated at the user-month level and analyzed using unsupervised clustering techniques. Our analysis identifies four distinct groups characterized by different emotional profiles and dominant coping orientations. These states exhibit meaningful correspondences with established theoretical frameworks, including the Coping Orientations to Problems Experienced model and the Patient Health Engagement model. Our findings demonstrate that large-scale textual data from online communities can provide interpretable insights into coping behaviors and engagement patterns, offering a complementary perspective to traditional approaches for studying mental health.
Suggested Citation
Virginia Morini & Salvatore Citraro & Elena Sajno & Maria Sansoni & Giuseppe Riva & Massimo Stella & Giulio Rossetti, 2026.
"Reddit Depression Communities as Spaces of Emotion Regulation: A Data-Informed Analysis of Coping and Engagement,"
Future Internet, MDPI, vol. 18(4), pages 1-23, April.
Handle:
RePEc:gam:jftint:v:18:y:2026:i:4:p:198-:d:1915931
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