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Mental health challenges are thought to afflict around 10% of the global population each year, with many going untreated due to stigma and limited access to services.
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Suicide in children and adolescents in England and Wales 1970–1998
G. McClure · 2001
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The world health report: Mental disorders affect one in four people
W. H. Organization · 2001
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P. S. Dodds, J. R. Minot, M. V. Arnold, T. Alshaabi, J. L. Adams, D. R. Dewhurst, T. J. Gray, M. R. Frank, A. J. Reagan, and C. M. Danforth · 2002
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On the stigma of mental illness
P. Corrigan and A. B. Bink · 2005
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250 labels used to stigmatise people with mental illness
D. Rose, G. Thornicroft, V. Pinfold, and A. Kassam · 2007
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Temporal patterns of happiness and information in a global social network: Hedonometrics and Twitter
P. S. Dodds, K. D. Harris, I. M. Kloumann, C. A. Bliss, and C. M. Danforth · 2011
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It’s easier for Americans to access guns than mental health services, 2012
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The paradox of mental health: Over-treatment and under-recognition
P. M. Editors et al · 2013
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Predicting depression via social media
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Characterizing and predicting postpartum depression from shared Facebook data
M. De Choudhury, S. Counts, E. J. Horvitz, and A. Hoff · 2014
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Quantifying mental health signals in Twitter
G. Coppersmith, M. Dredze, and C. Harman · 2014
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Use of Twitter to monitor attitudes toward depression and schizophrenia: An exploratory study
N. J. Reavley and P. D. Pilkington · 2014
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The scope and concerns of public health
R. Detels and C. C. Tan · 2015
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From ADHD to SAD: Analyzing the language of mental health on Twitter through self-reported diagnoses
G. Coppersmith, M. Dredze, C. Harman, and K. Hollingshead · 2015
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Social media, big data, and mental health: Current advances and ethical implications
M. Conway and D. O’Connor · 2016
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Discovering shifts to suicidal ideation from mental health content in social media
M. De Choudhury, E. Kiciman, M. Dredze, G. Coppersmith, and M. Kumar · 2016
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Large-scale analysis of counseling conversations: An application of natural language processing to mental health
T. Althoff, K. Clark, and J. Leskovec · 2016
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Forecasting the onset and course of mental illness with Twitter data
A. G. Reece, A. J. Reagan, K. L. Lix, P. S. Dodds, C. M. Danforth, and E. J. Langer · 2017
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Flattening the mental health curve: COVID-19 stay-at-home orders are associated with alterations in mental health search behavior in the United States
N. C. Jacobson, D. Lekkas, G. Price, M. V. Heinz, M. Song, A. J. O’Malley, and P. J. Barr · 2020
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Inside out and outside in: How the COVID-19 pandemic affects self-disclosure on social media
T. Nabity-Grover, C. M. Cheung, and J. B. Thatcher · 2020
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Social media and mental health: Benefits, risks, and opportunities for research and practice
J. A. Naslund, A. Bondre, J. Torous, and K. A. Aschbrenner · 2020
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The human in emotion recognition on social media: Attitudes, outcomes, risks
N. Andalibi and J. Buss · 2020
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Lifestyle and mental health disruptions during COVID-19
O. Giuntella, K. Hyde, S. Saccardo, and S. Sadoff · 2021
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Instagram photos reveal predictive markers of depression
A. G. Reece and C. M. Danforth · 2017
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California families claim ‘13 Reasons Why’ triggered teens’ suicides
K. Kindelan and S. Ghebremedhin · 2017
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Mental health, 2018
H. Ritchie and M. Roser · 2018
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Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017
S. L. James, D. Abate, K. H. Abate, S. M. Abay, C. Abbafati, N. Abbasi, H. Abbastabar, F. Abd-Allah, J. Abdela, A. Abdelalim, et al · 2018
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Sentiment analysis of health care tweets: Review of the methods used
S. Gohil, S. Vuik, and A. Darzi · 2018
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Detecting depression stigma on social media: A linguistic analysis
A. Li, D. Jiao, and T. Zhu · 2018
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A taxonomy of ethical tensions in inferring mental health states from social media
S. Chancellor, M. L. Birnbaum, E. D. Caine, V. M. Silenzio, and M. De Choudhury · 2019
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Increase in suicidal thinking during COVID-19
R. G. Fortgang, S. B. Wang, A. J. Millner, A. Reid-Russell, A. L. Beukenhorst, E. M. Kleiman, K. H. Bentley, K. L. Zuromski, M. Al-Suwaidi, S. A. Bird, et al · 2021
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Available online at https://www.crisistextline.org/everybody-hurts/
Everybody hurts, 2021 · 2021
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Doomscrolling during COVID-19: The negative association between daily social and traditional media consumption and mental health symptoms during the COVID-19 pandemic, 2021
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Distress disclosure across social media platforms during the COVID-19 pandemic: Untangling the effects of platforms, affordances, and audiences
R. Zhang, N. N. Bazarova, and M. Reddy · 2021
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Individuals with depression express more distorted thinking on social media
K. C. Bathina, M. Ten Thij, L. Lorenzo-Luaces, L. A. Rutter, and J. Bollen · 2021
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Data subjects’ conceptualizations of and attitudes toward automatic emotion recognition-enabled wellbeing interventions on social media
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Storywrangler: A massive exploratorium for sociolinguistic, cultural, socioeconomic, and political timelines using Twitter
T. Alshaabi, J. L. Adams, M. V. Arnold, J. R. Minot, D. R. Dewhurst, A. J. Reagan, C. M. Danforth, and P. S. Dodds · 2021
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Generalized word shift graphs: A method for visualizing and explaining pairwise comparisons between texts
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T. Alshaabi, D. R. Dewhurst, J. R. Minot, M. V. Arnold, J. L. Adams, C. M. Danforth, and P. S. Dodds · 2021
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