Abstract
Background: Social media provides the potential to engage a wide audience about scientific research, including the public. However little empirical research exists to guide health scientists regarding what works and how to optimize impact. We examined the social media campaign #datasaveslives, which was established in 2014 to highlight positive examples of the use and reuse of health data in research.
Objective: The study aimed to examine how the #datasaveslives hashtag was used on social media, how often and by whom; thus, the study aimed to provide insights into the impact of a major social media campaign in the UK health informatics research community and further afield.
Methods: We analyzed all publicly available posts (tweets) between 1 September 2016 and 31 August 2017 on the microblogging platform Twitter that included the hashtag #datasaveslives (n=13,895). Using a combination of qualitative and quantitative analyses, we determined the frequency and purpose of tweets. Social network analysis was used to analyze and visualize tweet sharing (‘retweet’) networks among hashtag users.
Results: Overall, we found 4,175 original tweets and 9,720 retweets featuring #datasaveslives by 3,649 unique Twitter users. In total, 2,756 (66.0%) of original posts were retweeted at least once. Higher frequencies of tweets were observed during the weeks of prominent policy publications, popular conferences and public engagement events. Cluster analysis based on retweet relationships revealed an interconnected series of groups of #datasaveslives users in academia, health services and policy, and charities and patient networks. Thematic analysis of tweets showed that #datasaveslives was used for a broader range of purposes than indexing information, including event reporting, encouraging participation and action, and showing personal support for data sharing.
Conclusions: This study shows that a hashtag-based social media campaign was effective in encouraging a wide audience of stakeholders to disseminate positive examples of health research. Furthermore, the findings suggest the campaign supported community-building and bridging practices within and between the interdisciplinary sectors related to the field of health data science and encouraged individuals to demonstrate personal support for sharing health data.
Objective: The study aimed to examine how the #datasaveslives hashtag was used on social media, how often and by whom; thus, the study aimed to provide insights into the impact of a major social media campaign in the UK health informatics research community and further afield.
Methods: We analyzed all publicly available posts (tweets) between 1 September 2016 and 31 August 2017 on the microblogging platform Twitter that included the hashtag #datasaveslives (n=13,895). Using a combination of qualitative and quantitative analyses, we determined the frequency and purpose of tweets. Social network analysis was used to analyze and visualize tweet sharing (‘retweet’) networks among hashtag users.
Results: Overall, we found 4,175 original tweets and 9,720 retweets featuring #datasaveslives by 3,649 unique Twitter users. In total, 2,756 (66.0%) of original posts were retweeted at least once. Higher frequencies of tweets were observed during the weeks of prominent policy publications, popular conferences and public engagement events. Cluster analysis based on retweet relationships revealed an interconnected series of groups of #datasaveslives users in academia, health services and policy, and charities and patient networks. Thematic analysis of tweets showed that #datasaveslives was used for a broader range of purposes than indexing information, including event reporting, encouraging participation and action, and showing personal support for data sharing.
Conclusions: This study shows that a hashtag-based social media campaign was effective in encouraging a wide audience of stakeholders to disseminate positive examples of health research. Furthermore, the findings suggest the campaign supported community-building and bridging practices within and between the interdisciplinary sectors related to the field of health data science and encouraged individuals to demonstrate personal support for sharing health data.
| Original language | English |
|---|---|
| Journal | JMIR |
| DOIs | |
| Publication status | Published - 16 Jan 2021 |
