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Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review

Background: Text-mining techniques are advancing all the time and vast corpora of social media text can be analyzed for users' views and experiences related to their health. There is great promise for new insights into health issues such as drug side effects and spread of disease, as well as pa...

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Detalles Bibliográficos
Autores principales: Ford, Elizabeth, Shepherd, Scarlett, Jones, Kerina, Hassan, Lamiece
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8521805/
https://www.ncbi.nlm.nih.gov/pubmed/34713062
http://dx.doi.org/10.3389/fdgth.2020.592237
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author Ford, Elizabeth
Shepherd, Scarlett
Jones, Kerina
Hassan, Lamiece
author_facet Ford, Elizabeth
Shepherd, Scarlett
Jones, Kerina
Hassan, Lamiece
author_sort Ford, Elizabeth
collection PubMed
description Background: Text-mining techniques are advancing all the time and vast corpora of social media text can be analyzed for users' views and experiences related to their health. There is great promise for new insights into health issues such as drug side effects and spread of disease, as well as patient experiences of health conditions and health care. However, this emerging field lacks ethical consensus and guidance. We aimed to bring together a comprehensive body of opinion, views, and recommendations in this area so that academic researchers new to the field can understand relevant ethical issues. Methods: After registration of a protocol in PROSPERO, three parallel systematic searches were conducted, to identify academic articles comprising commentaries, opinion, and recommendations on ethical practice in social media text mining for health research and gray literature guidelines and recommendations. These were integrated with social media users' views from qualitative studies. Papers and reports that met the inclusion criteria were analyzed thematically to identify key themes, and an overarching set of themes was deduced. Results: A total of 47 reports and articles were reviewed, and eight themes were identified. Commentators suggested that publicly posted social media data could be used without consent and formal research ethics approval, provided that the anonymity of users is ensured, although we note that privacy settings are difficult for users to navigate on some sites. Even without the need for formal approvals, we note ethical issues: to actively identify and minimize possible harms, to conduct research for public benefit rather than private gain, to ensure transparency and quality of data access and analysis methods, and to abide by the law and terms and conditions of social media sites. Conclusion: Although social media text mining can often legally and reasonably proceed without formal ethics approvals, we recommend improving ethical standards in health-related research by increasing transparency of the purpose of research, data access, and analysis methods; consultation with social media users and target groups to identify and mitigate against potential harms that could arise; and ensuring the anonymity of social media users.
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spelling pubmed-85218052021-10-27 Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review Ford, Elizabeth Shepherd, Scarlett Jones, Kerina Hassan, Lamiece Front Digit Health Digital Health Background: Text-mining techniques are advancing all the time and vast corpora of social media text can be analyzed for users' views and experiences related to their health. There is great promise for new insights into health issues such as drug side effects and spread of disease, as well as patient experiences of health conditions and health care. However, this emerging field lacks ethical consensus and guidance. We aimed to bring together a comprehensive body of opinion, views, and recommendations in this area so that academic researchers new to the field can understand relevant ethical issues. Methods: After registration of a protocol in PROSPERO, three parallel systematic searches were conducted, to identify academic articles comprising commentaries, opinion, and recommendations on ethical practice in social media text mining for health research and gray literature guidelines and recommendations. These were integrated with social media users' views from qualitative studies. Papers and reports that met the inclusion criteria were analyzed thematically to identify key themes, and an overarching set of themes was deduced. Results: A total of 47 reports and articles were reviewed, and eight themes were identified. Commentators suggested that publicly posted social media data could be used without consent and formal research ethics approval, provided that the anonymity of users is ensured, although we note that privacy settings are difficult for users to navigate on some sites. Even without the need for formal approvals, we note ethical issues: to actively identify and minimize possible harms, to conduct research for public benefit rather than private gain, to ensure transparency and quality of data access and analysis methods, and to abide by the law and terms and conditions of social media sites. Conclusion: Although social media text mining can often legally and reasonably proceed without formal ethics approvals, we recommend improving ethical standards in health-related research by increasing transparency of the purpose of research, data access, and analysis methods; consultation with social media users and target groups to identify and mitigate against potential harms that could arise; and ensuring the anonymity of social media users. Frontiers Media S.A. 2021-01-26 /pmc/articles/PMC8521805/ /pubmed/34713062 http://dx.doi.org/10.3389/fdgth.2020.592237 Text en Copyright © 2021 Ford, Shepherd, Jones and Hassan. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Digital Health
Ford, Elizabeth
Shepherd, Scarlett
Jones, Kerina
Hassan, Lamiece
Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review
title Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review
title_full Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review
title_fullStr Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review
title_full_unstemmed Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review
title_short Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review
title_sort toward an ethical framework for the text mining of social media for health research: a systematic review
topic Digital Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8521805/
https://www.ncbi.nlm.nih.gov/pubmed/34713062
http://dx.doi.org/10.3389/fdgth.2020.592237
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