TY - GEN
T1 - Mental Health Coping Stories on Social Media
T2 - 2023 World Wide Web Conference, WWW 2023
AU - Yuan, Yunhao
AU - Saha, Koustuv
AU - Keller, Barbara
AU - Isometsä, Erkki Tapio
AU - Aledavood, Talayeh
N1 - Publisher Copyright:
© 2023 Owner/Author.
PY - 2023/4/30
Y1 - 2023/4/30
N2 - The Papageno effect concerns how media can play a positive role in preventing and mitigating suicidal ideation and behaviors. With the increasing ubiquity and widespread use of social media, individuals often express and share lived experiences and struggles with mental health. However, there is a gap in our understanding about the existence and effectiveness of the Papageno effect in social media, which we study in this paper. In particular, we adopt a causal-inference framework to examine the impact of exposure to mental health coping stories on individuals on Twitter. We obtain a Twitter dataset with ∼2M posts by ∼10K individuals. We consider engaging with coping stories as the Treatment intervention, and adopt a stratified propensity score approach to find matched cohorts of Treatment and Control individuals. We measure the psychosocial shifts in affective, behavioral, and cognitive outcomes in longitudinal Twitter data before and after engaging with the coping stories. Our findings reveal that, engaging with coping stories leads to decreased stress and depression, and improved expressive writing, diversity, and interactivity. Our work discusses the practical and platform design implications in supporting mental wellbeing.
AB - The Papageno effect concerns how media can play a positive role in preventing and mitigating suicidal ideation and behaviors. With the increasing ubiquity and widespread use of social media, individuals often express and share lived experiences and struggles with mental health. However, there is a gap in our understanding about the existence and effectiveness of the Papageno effect in social media, which we study in this paper. In particular, we adopt a causal-inference framework to examine the impact of exposure to mental health coping stories on individuals on Twitter. We obtain a Twitter dataset with ∼2M posts by ∼10K individuals. We consider engaging with coping stories as the Treatment intervention, and adopt a stratified propensity score approach to find matched cohorts of Treatment and Control individuals. We measure the psychosocial shifts in affective, behavioral, and cognitive outcomes in longitudinal Twitter data before and after engaging with the coping stories. Our findings reveal that, engaging with coping stories leads to decreased stress and depression, and improved expressive writing, diversity, and interactivity. Our work discusses the practical and platform design implications in supporting mental wellbeing.
KW - causal inference
KW - mental health
KW - natural language
KW - Papageno effect
KW - social media
KW - suicidal ideation
UR - http://www.scopus.com/inward/record.url?scp=85159263839&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85159263839&partnerID=8YFLogxK
U2 - 10.1145/3543507.3583350
DO - 10.1145/3543507.3583350
M3 - Conference contribution
AN - SCOPUS:85159263839
T3 - ACM Web Conference 2023 - Proceedings of the World Wide Web Conference, WWW 2023
SP - 2677
EP - 2685
BT - ACM Web Conference 2023 - Proceedings of the World Wide Web Conference, WWW 2023
PB - Association for Computing Machinery
Y2 - 30 April 2023 through 4 May 2023
ER -