Mental Health Discourse on reddit: Self-Disclosure, Social Support, and Anonymity

By M. de Choudhury, Sushovan De. International Conference on Web and Social Media, 2014

899 citations recorded by the source corpus.

Social media is continually emerging as a platform of information exchange around health challenges. We study mental health discourse on the popular social media:reddit. Building on findings about health information seeking and sharing practices in online forums, and social media like Twitter, we address three research challenges. First, we present a characterization of self-disclosure inmental illness communities on reddit. We observe individuals discussing a variety of concerns ranging from the daily grind to specific queries about diagnosis and treatment. Second, we build a statistical model to examine the factors that drive social support on mental health reddit communities. We also develop language models to characterize mental health social support, which are observed to bear emotional, informational, instrumental, and prescriptive information. Finally, we study disinhibition in the light of the dissociative anonymity that reddit’s throwaway accounts provide. Apart from promoting open conversations,such anonymity surprisingly is found to gather feedback that is more involving and emotionally engaging. Our findings reveal, for the first time, the kind of unique information needs that a social media like reddit might be fulfilling when it comes to a stigmatic illness. They also expand our understanding of the role of the social web in behavioral therapy.

Subfields: Social Psychology, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/e58943b8d656fbb07a14f36b28ae211da74992a9

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Citations in the corpus

"I Hear You, I Feel You": Encouraging Deep Self-disclosure through a Chatbot (2020, background): “For example, people’s self-disclosure on social media helps them release their stress, depression, and anxiety through these technologies [10, 3].”
Beyond Screen Time: Identity Development in the Digital Age (2020, background): “For instance, public social media text applications (e.g. Facebook, Twitter) could be used to track contamination themes as they emerge naturalistically in young people’s everyday digital discourse (e.g. De Choudhury & De, 2014; De Choudhury et al., 2016).”
Detecting Changes in Suicide Content Manifested in Social Media Following Celebrity Suicides (2015, background): “Measures belonging to all of these attribute categories are largely based on the psycholinguistic lexicon LIWC [40], and were motivated from prior literature that examine associations between the behavioral expression of individuals and their responses to traumatic context and crises, including vuln”
Understanding Social Media Disclosures of Sexual Abuse Through the Lenses of Support Seeking and Anonymity (2016, methodology): “work [20,50] to identify those dedicated to discourse and support around sexual abuse.”
It’s going to be okay: Measuring Access to Support in Online Communities (2018, neutral): “Prior works have also examined the language of support in online support forums for health-related issues (Biyani et al., 2014; Wang et al., 2012; De Choudhury and De, 2014; Althoff et al., 2016; De Choudhury and Kiciman, 2017), often with the aim of improving people’s access.”
Sensitive Self-disclosures, Responses, and Social Support on Instagram: The Case of #Depression (2017, background): “Although social support exists in online mental health communities such as subreddits [21] or other health support groups, those are dedicated spaces rather than emergent groups coalescing around use of one or most often more public hashtags.”
Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances (2018, neutral): “Such texts sources include social media and online fora [18–21] as well as doctor-patient interactions [22–24] and online therapy [25], to mention a few examples.”
Leveraging Large Language Models for Mental Health Prediction via Online Text Data (2023, background): “Online platforms, especially social media platforms, have been acknowledged as a promising lens that is capable of revealing insights into the psychological states, health, and well-being of both individuals and populations [14, 22, 25, 36, 63].”
Depression and Self-Harm Risk Assessment in Online Forums (2017, background): “Research has demonstrated that forums are powerful platforms for self-disclosure and social support seeking around mental health concerns (De Choudhury and De, 2014; Manikonda and De Choudhury, 2017).”
Natural language processing in mental health applications using non-clinical texts† (2017, background): “For example, the nature of personal disclosure has been studied on Reddit (De Choudhury and De 2014), an online media platform similar to discussion forums but with an optional “throwaway” account type that improves anonymity.”
Discovering Shifts to Suicidal Ideation from Mental Health Content in Social Media (2016, neutral): “The choice of these measures is motivated by literature that examines associations between the behavioral expression of individuals and their responses to crises, including vulnerability due to mental illness [13, 23].”
Community-level Research on Suicidality Prediction in a Secure Environment: Overview of the CLPsych 2021 Shared Task (2021, methodology): “…data has led to a proliferation of proxy variables taken from publicly available data rather than ground-truth clinical variables or real-world outcomes (e.g. De Choudhury and De, 2014; Coppersmith et al., 2014; Yates et al., 2017; Shing et al., 2018; Cohan et al., 2018; Thorstad and Wolff, 2019).”
Artificial Intelligence for Mental Healthcare: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom (2021, background): “Examining the content, language, and consumption patterns of social media provide novel insights into relationships and communication, as well as create new opportunities for seeking help (73,74).”
Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications (2019, background): “topic-specific discussions has also attracted much research interest for studying mental health issues [89] and suicidal”