No Cover Image

Journal article 521 views 157 downloads

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

Elizabeth Ford, Scarlett Shepherd, Kerina Jones Orcid Logo, Lamiece Hassan

Frontiers in Digital Health, Volume: 2

Swansea University Author: Kerina Jones Orcid Logo

  • 57539.pdf

    PDF | Version of Record

    Copyright © 2021 Ford, Shepherd, Jones and Hassan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY)

    Download (1013.33KB)

Check full text

DOI (Published version): 10.3389/fdgth.2020.592237

Abstract

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...

Full description

Published in: Frontiers in Digital Health
ISSN: 2673-253X
Published: Frontiers Media SA 2021
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa57539
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2021-08-05T14:30:26Z
last_indexed 2021-09-09T03:20:58Z
id cronfa57539
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2021-09-08T13:59:57.8369880</datestamp><bib-version>v2</bib-version><id>57539</id><entry>2021-08-05</entry><title>Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review</title><swanseaauthors><author><sid>c13b3cd0a6f8cbac2e461b54b3cdd839</sid><ORCID>0000-0001-8164-3718</ORCID><firstname>Kerina</firstname><surname>Jones</surname><name>Kerina Jones</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2021-08-05</date><deptcode>HDAT</deptcode><abstract>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.</abstract><type>Journal Article</type><journal>Frontiers in Digital Health</journal><volume>2</volume><journalNumber/><paginationStart/><paginationEnd/><publisher>Frontiers Media SA</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>2673-253X</issnElectronic><keywords>social media, text-mining, health research, natural language processing, ethics</keywords><publishedDay>26</publishedDay><publishedMonth>1</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-01-26</publishedDate><doi>10.3389/fdgth.2020.592237</doi><url/><notes/><college>COLLEGE NANME</college><department>Health Data Science</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>HDAT</DepartmentCode><institution>Swansea University</institution><apcterm>External research funder(s) paid the OA fee (includes OA grants disbursed by the Library)</apcterm><funders>UKRI, MRC</funders><projectreference>MR/S004025/1</projectreference><lastEdited>2021-09-08T13:59:57.8369880</lastEdited><Created>2021-08-05T15:29:17.3445676</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Medicine</level></path><authors><author><firstname>Elizabeth</firstname><surname>Ford</surname><order>1</order></author><author><firstname>Scarlett</firstname><surname>Shepherd</surname><order>2</order></author><author><firstname>Kerina</firstname><surname>Jones</surname><orcid>0000-0001-8164-3718</orcid><order>3</order></author><author><firstname>Lamiece</firstname><surname>Hassan</surname><order>4</order></author></authors><documents><document><filename>57539__20562__f2e74752105b4bdc9fea93c54e2a449c.pdf</filename><originalFilename>57539.pdf</originalFilename><uploaded>2021-08-05T15:30:46.3314225</uploaded><type>Output</type><contentLength>1037648</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>Copyright &#xA9; 2021 Ford, Shepherd, Jones and Hassan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY)</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>http://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 2021-09-08T13:59:57.8369880 v2 57539 2021-08-05 Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review c13b3cd0a6f8cbac2e461b54b3cdd839 0000-0001-8164-3718 Kerina Jones Kerina Jones true false 2021-08-05 HDAT 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. Journal Article Frontiers in Digital Health 2 Frontiers Media SA 2673-253X social media, text-mining, health research, natural language processing, ethics 26 1 2021 2021-01-26 10.3389/fdgth.2020.592237 COLLEGE NANME Health Data Science COLLEGE CODE HDAT Swansea University External research funder(s) paid the OA fee (includes OA grants disbursed by the Library) UKRI, MRC MR/S004025/1 2021-09-08T13:59:57.8369880 2021-08-05T15:29:17.3445676 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Elizabeth Ford 1 Scarlett Shepherd 2 Kerina Jones 0000-0001-8164-3718 3 Lamiece Hassan 4 57539__20562__f2e74752105b4bdc9fea93c54e2a449c.pdf 57539.pdf 2021-08-05T15:30:46.3314225 Output 1037648 application/pdf Version of Record true Copyright © 2021 Ford, Shepherd, Jones and Hassan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) true eng http://creativecommons.org/licenses/by/4.0/
title Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review
spellingShingle Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review
Kerina Jones
title_short 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_sort Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review
author_id_str_mv c13b3cd0a6f8cbac2e461b54b3cdd839
author_id_fullname_str_mv c13b3cd0a6f8cbac2e461b54b3cdd839_***_Kerina Jones
author Kerina Jones
author2 Elizabeth Ford
Scarlett Shepherd
Kerina Jones
Lamiece Hassan
format Journal article
container_title Frontiers in Digital Health
container_volume 2
publishDate 2021
institution Swansea University
issn 2673-253X
doi_str_mv 10.3389/fdgth.2020.592237
publisher Frontiers Media SA
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
document_store_str 1
active_str 0
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.
published_date 2021-01-26T04:13:21Z
_version_ 1763753907376357376
score 11.016235

Similar Items