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Use of the Hashtag #DataSavesLives on Twitter: Exploratory and Thematic Analysis
BACKGROUND: “Data Saves Lives” is a public engagement campaign that highlights the benefits of big data research and aims to establish public trust for this emerging research area. OBJECTIVE: This study explores how the hashtag #DataSavesLives is used on Twitter. We focused on the period when the UK...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9709666/ https://www.ncbi.nlm.nih.gov/pubmed/36378518 http://dx.doi.org/10.2196/38232 |
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author | Teodorowski, Piotr Rodgers, Sarah E Fleming, Kate Frith, Lucy |
author_facet | Teodorowski, Piotr Rodgers, Sarah E Fleming, Kate Frith, Lucy |
author_sort | Teodorowski, Piotr |
collection | PubMed |
description | BACKGROUND: “Data Saves Lives” is a public engagement campaign that highlights the benefits of big data research and aims to establish public trust for this emerging research area. OBJECTIVE: This study explores how the hashtag #DataSavesLives is used on Twitter. We focused on the period when the UK government and its agencies adopted #DataSavesLives in an attempt to support their plans to set up a new database holding National Health Service (NHS) users’ medical data. METHODS: Public tweets published between April 19 and July 15, 2021, using the hashtag #DataSavesLives were saved using NCapture for NVivo 12. All tweets were coded twice. First, each tweet was assigned a positive, neutral, or negative attitude toward the campaign. Second, inductive thematic analysis was conducted. The results of the thematic analysis were mapped under 3 models of public engagement: deficit, dialogue, and participatory. RESULTS: Of 1026 unique tweets available for qualitative analysis, discussion around #DataSavesLives was largely positive (n=716, 69.8%) or neutral (n=276, 26.9%) toward the campaign with limited negative attitudes (n=34, 3.3%). Themes derived from the #DataSavesLives debate included ethical sharing, proactively engaging the public, coproducing knowledge with the public, harnessing potential, and gaining an understanding of big data research. The Twitter discourse was largely positive toward the campaign. The hashtag is predominantly used by similar-minded Twitter users to share information about big data projects and to spread positive messages about big data research when there are public controversies. The hashtag is generally used by organizations and people supportive of big data research. Tweet authors recognize that the public should be proactively engaged and involved in big data projects. The campaign remains UK centric. The results indicate that the communication around big data research is driven by the professional community and remains 1-way as members of the public rarely use the hashtag. CONCLUSIONS: The results demonstrate the potential of social media but draws attention to hashtag usage being generally confined to “Twitter bubbles”: groups of similar-minded Twitter users. |
format | Online Article Text |
id | pubmed-9709666 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-97096662022-12-01 Use of the Hashtag #DataSavesLives on Twitter: Exploratory and Thematic Analysis Teodorowski, Piotr Rodgers, Sarah E Fleming, Kate Frith, Lucy J Med Internet Res Original Paper BACKGROUND: “Data Saves Lives” is a public engagement campaign that highlights the benefits of big data research and aims to establish public trust for this emerging research area. OBJECTIVE: This study explores how the hashtag #DataSavesLives is used on Twitter. We focused on the period when the UK government and its agencies adopted #DataSavesLives in an attempt to support their plans to set up a new database holding National Health Service (NHS) users’ medical data. METHODS: Public tweets published between April 19 and July 15, 2021, using the hashtag #DataSavesLives were saved using NCapture for NVivo 12. All tweets were coded twice. First, each tweet was assigned a positive, neutral, or negative attitude toward the campaign. Second, inductive thematic analysis was conducted. The results of the thematic analysis were mapped under 3 models of public engagement: deficit, dialogue, and participatory. RESULTS: Of 1026 unique tweets available for qualitative analysis, discussion around #DataSavesLives was largely positive (n=716, 69.8%) or neutral (n=276, 26.9%) toward the campaign with limited negative attitudes (n=34, 3.3%). Themes derived from the #DataSavesLives debate included ethical sharing, proactively engaging the public, coproducing knowledge with the public, harnessing potential, and gaining an understanding of big data research. The Twitter discourse was largely positive toward the campaign. The hashtag is predominantly used by similar-minded Twitter users to share information about big data projects and to spread positive messages about big data research when there are public controversies. The hashtag is generally used by organizations and people supportive of big data research. Tweet authors recognize that the public should be proactively engaged and involved in big data projects. The campaign remains UK centric. The results indicate that the communication around big data research is driven by the professional community and remains 1-way as members of the public rarely use the hashtag. CONCLUSIONS: The results demonstrate the potential of social media but draws attention to hashtag usage being generally confined to “Twitter bubbles”: groups of similar-minded Twitter users. JMIR Publications 2022-11-15 /pmc/articles/PMC9709666/ /pubmed/36378518 http://dx.doi.org/10.2196/38232 Text en ©Piotr Teodorowski, Sarah E Rodgers, Kate Fleming, Lucy Frith. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 15.11.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Teodorowski, Piotr Rodgers, Sarah E Fleming, Kate Frith, Lucy Use of the Hashtag #DataSavesLives on Twitter: Exploratory and Thematic Analysis |
title | Use of the Hashtag #DataSavesLives on Twitter: Exploratory and Thematic Analysis |
title_full | Use of the Hashtag #DataSavesLives on Twitter: Exploratory and Thematic Analysis |
title_fullStr | Use of the Hashtag #DataSavesLives on Twitter: Exploratory and Thematic Analysis |
title_full_unstemmed | Use of the Hashtag #DataSavesLives on Twitter: Exploratory and Thematic Analysis |
title_short | Use of the Hashtag #DataSavesLives on Twitter: Exploratory and Thematic Analysis |
title_sort | use of the hashtag #datasaveslives on twitter: exploratory and thematic analysis |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9709666/ https://www.ncbi.nlm.nih.gov/pubmed/36378518 http://dx.doi.org/10.2196/38232 |
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