Ethical research protocols for social media health research
Open accessAbstract
Social media have transformed datadriven research in political science, the social sciences, health, and medicine.Since health research often touches on sensitive topics that relate to ethics of treatment and patient privacy, similar ethical considerations should be acknowledged when using social media data in health research.While much has been said regarding the ethical considerations of social media research, health research leads to an additional set of concerns.We provide practical suggestions in the form of guidelines for researchers working with social media data in health research.These guidelines can inform an IRB proposal for researchers new to social media health research.
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Data, tools, and inferences obtained for one purpose can be used for another purpose.
“Thus, data, tools, and inferences obtained for one purpose can be used for another purpose (Hovy and Spruit, 2016; Benton et al., 2017)”
From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Benton et al., 2017
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References 32 · Cited by 219
- Authors
- Benton, A., Coppersmith, G., & Dredze, M.
- Affiliations
- Johns Hopkins University (US)
- Venue
- Proceedings of the First ACL Workshop on Ethics in Natural Language Processing
- Published
- 2017
- Pages
- 94-102
- OpenAlex
- W2741004402
- Cited by
- 219
- References
- 32
- Citations by year
- 2026: 15 · 2025: 15 · 2024: 22 · 2023: 23 · 2022: 44 · 2021: 47 · 2020: 24 · 2019: 15 · 2018: 11 · 2017: 3
- FWCI
- 171.08
- Type
- conference paper
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Topics
- Social Sciences › Health › Social Media in Health Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics in Clinical Research
- Social Sciences › Sociology and Political Science › Focus Groups and Qualitative Methods
- Keywords
- research ethics, patient privacy, informed consent, research ethics committees, research guidelines, sensitive health data, data-driven research
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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