Detecting depression and mental illness on social media: an integrative review
By Sharath Chandra Guntuku, David B. Yaden, Margaret L. Kern, Lyle Ungar, Johannes C. Eichstaedt. 2017
685 citations recorded by the source corpus.
Subfields: Applied Psychology, Experimental and Cognitive Psychology, Social Psychology
View Paper: https://www.semanticscholar.org/paper/c6bbfcfc16e3dcb33b0463a95df44d543838c76d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Applied Psychology
- Margaret L. Kern
- Paige L. Williams
- L. Oades
- Lucie Flekova
- John B. Torous
- L. Waters
- T. Lomas
- Adam M. Grant
In Experimental and Cognitive Psychology
- Satrajit S. Ghosh
- Jure Leskovec
- Dan Jurafsky
- Roi Reichart
- L. Oades
- Lucie Flekova
- Margaret L. Kern
- John B. Torous
In Social Psychology
- L. Waters
- Margaret L. Kern
- Lucie Flekova
- Paige L. Williams
- Jure Leskovec
- Dan Jurafsky
- Roi Reichart
- L. Oades
Citations in the corpus
- Natural Language Processing Reveals Vulnerable Mental Health Support Groups and Heightened Health Anxiety on Reddit During COVID-19: Observational Study (2020, background): “Using natural language processing (NLP) to infer mental states of individuals from their social media posts is a growing field (for reviews, see [5,6]).”
- Depression detection from social network data using machine learning techniques (2018, background): “There is growing body of literature that analyses the properties of depression [9–12].”
- Third wave positive psychology: broadening towards complexity (2020, background): “…of power differentials on community engagement (Danescu-Niculescu-Mizil et al., 2013); personal values (Boyd et al., 2015); emotions (Bollen et al., 2011; Strapparava & Mihalcea, 2008); and psychological traits (Guntuku et al., 2017; Mitchell et al., 2015; Park et al., 2015; Sagi & Dehghani, 2014).”
- The Role of AI in Hospitals and Clinics: Transforming Healthcare in the 21st Century (2024, background): “By monitoring patterns in speech [51], behavior [52], and social media activity [53,54], AI tools can help in identifying the onset of mental health issues and suggest interventions tailored to the individual’s unique situation.”
- Returning the N to NLP: Towards Contextually Personalized Classification Models (2020, background): “…2010), political preferences (Volkova et al., 2014), socio-economic status (Preot¸iuc-Pietro et al., 2015), impact (Lampos et al., 2014), and a range of psychological traits and issues (Schwartz et al., 2013; Park et al., 2015; Sum-ner et al., 2012; Guntuku et al., 2017; Coppersmith et al., 2014).”
- The Hitchhiker’s Guide to Computational Linguistics in Suicide Prevention (2021, background): “…ideation/behaviors (for updated reviews, see Bernert et al., 2020; Burke et al., 2019; Ji et al., 2020) and depression (Giuntini et al., 2020; Guntuku et al., 2017), one of the most dominant risk factors for suicide behaviors and a major psychiatric and economic burden by itself (D. A. Clark…”
- Detection of Depression-Related Posts in Reddit Social Media Forum (2019, background): “[15] summarizes several iterations of depression detection tasks in computational linguistics.”
- Community Interaction and Conflict on the Web (2018, background): “…primarily on controversies [4, 13, 20, 21, 45, 52] and anti-social behavior, in the form of trolling [11, 12, 42], sockpup-petry [39], harassment and cyberbullying [8, 23, 32, 35, 55, 66, 79], vandalism [43], hate speech [9, 15, 51, 56, 72], and others [17, 24, 40, 41, 44, 46, 54, 68, 78, 81].”