Social media, big data, and mental health: current advances and ethical implications
Open accessAbstract
Mental health (including substance abuse) is the fifth greatest contributor to the global burden of disease, with an economic cost estimated to be US $2.5 trillion in 2010, and expected to double by 2030. Developing information systems to support and strengthen population-level mental health monitoring forms a core part of the World Health Organization's Comprehensive Action Plan 2013-2020. In this paper, we review recent work that utilizes social media "big data" in conjunction with associated technologies like natural language processing and machine learning to address pressing problems in population-level mental health surveillance and research, focusing both on technological advances and core ethical challenges.
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Users generally expect their privacy to be respected online, and most feel their data should not be used for mental health research without their explicit consent.
“users generally expect their privacy to be respected online [37], with most feeling their data should not be used for mental health research without their explicit consent [34].”
From Operationalising ethics in artificial intelligence for healthcare: a framework for AI developers (2023) · cites this paper as [37]
Trust in AI for healthcare may be lost when AI have many false positive or negative results, are perceived to be incompetent, or make use of public data in a disrespectful way.
“Trust may be lost when AI have many false positive or negative results [41], are perceived to be incompetent [30], or make use of public data in a disrespectful way [37].”
From Operationalising ethics in artificial intelligence for healthcare: a framework for AI developers (2023) · cites this paper as [37]
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Flagged first, then by citations
Research works printed but not linked: 2
- [5]Lane J Stodden V Bender S Nissenbaum H Privacy, big data, and the public good Cambridge University Press 2014
- [54]Lopez S The Oxford Handbook of Positive Psychology Oxford University Press 2011
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“Regarding social media and mental health, users generally expect their privacy to be respected online [37], with most feeling their data should not be used for mental health research without their explicit consent [34].”
BackgroundConway, M., Hu, M., & Chapman, W. W. (2019) · Yearbook of Medical Informatics · doi:10.1055/s-0039-1677918 · Cited by 91 · see citing works
Self-citation
- Authors
- Conway, M., & O’Connor, D.
- Affiliations
- University of Utah (US)
- Wellcome Trust (GB)
- Corresponding author
- Conway, Mike
- ORCID
- Conway, Mike
- Venue
- Current Opinion in Psychology
- Publisher
- Elsevier BV
- Published
- 2016-06
- Volume
- 9
- Pages
- 77-82
- ISSN
- 2352-250X (ISSN-L)
- PMC
- PMC4815031
- OpenAlex
- W2250240141
- Cited by
- 231
- References
- 62
- Citations by year
- 2026: 9 · 2025: 20 · 2024: 20 · 2023: 23 · 2022: 32 · 2021: 46 · 2020: 28 · 2019: 18 · 2018: 18 · 2017: 14 · 2016: 3
- FWCI
- 2.78
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Current Opinion in Psychology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Library of Medicine (R00LM011393)
- Topics
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Health Sciences › Medicine › Epidemiology › Data-Driven Disease Surveillance
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Keywords
- social media, big data, mental health, substance abuse, natural language processing, machine learning, ethical implications, information systems, global burden of disease
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