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Trustworthy Health-Related Tweets on Social Media in Saudi Arabia: Tweet Metadata Analysis

BACKGROUND: Social media platforms play a vital role in the dissemination of health information. However, evidence suggests that a high proportion of Twitter posts (ie, tweets) are not necessarily accurate, and many studies suggest that tweets do not need to be accurate, or at least evidence based,...

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Detalles Bibliográficos
Autores principales: Albalawi, Yahya, Nikolov, Nikola S, Buckley, Jim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6914129/
https://www.ncbi.nlm.nih.gov/pubmed/31596242
http://dx.doi.org/10.2196/14731
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author Albalawi, Yahya
Nikolov, Nikola S
Buckley, Jim
author_facet Albalawi, Yahya
Nikolov, Nikola S
Buckley, Jim
author_sort Albalawi, Yahya
collection PubMed
description BACKGROUND: Social media platforms play a vital role in the dissemination of health information. However, evidence suggests that a high proportion of Twitter posts (ie, tweets) are not necessarily accurate, and many studies suggest that tweets do not need to be accurate, or at least evidence based, to receive traction. This is a dangerous combination in the sphere of health information. OBJECTIVE: The first objective of this study is to examine health-related tweets originating from Saudi Arabia in terms of their accuracy. The second objective is to find factors that relate to the accuracy and dissemination of these tweets, thereby enabling the identification of ways to enhance the dissemination of accurate tweets. The initial findings from this study and methodological improvements will then be employed in a larger-scale study that will address these issues in more detail. METHODS: A health lexicon was used to extract health-related tweets using the Twitter application programming interface and the results were further filtered manually. A total of 300 tweets were each labeled by two medical doctors; the doctors agreed that 109 tweets were either accurate or inaccurate. Other measures were taken from these tweets’ metadata to see if there was any relationship between the measures and either the accuracy or the dissemination of the tweets. The entire range of this metadata was analyzed using Python, version 3.6.5 (Python Software Foundation), to answer the research questions posed. RESULTS: A total of 34 out of 109 tweets (31.2%) in the dataset used in this study were classified as untrustworthy health information. These came mainly from users with a non-health care background and social media accounts that had no corresponding physical (ie, organization) manifestation. Unsurprisingly, we found that traditionally trusted health sources were more likely to tweet accurate health information than other users. Likewise, these provisional results suggest that tweets posted in the morning are more trustworthy than tweets posted at night, possibly corresponding to official and casual posts, respectively. Our results also suggest that the crowd was quite good at identifying trustworthy information sources, as evidenced by the number of times a tweet’s author was tagged as favorited by the community. CONCLUSIONS: The results indicate some initially surprising factors that might correlate with the accuracy of tweets and their dissemination. For example, the time a tweet was posted correlated with its accuracy, which may reflect a difference between professional (ie, morning) and hobbyist (ie, evening) tweets. More surprisingly, tweets containing a kashida—a decorative element in Arabic writing used to justify the text within lines—were more likely to be disseminated through retweets. These findings will be further assessed using data analysis techniques on a much larger dataset in future work.
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spelling pubmed-69141292020-01-02 Trustworthy Health-Related Tweets on Social Media in Saudi Arabia: Tweet Metadata Analysis Albalawi, Yahya Nikolov, Nikola S Buckley, Jim J Med Internet Res Original Paper BACKGROUND: Social media platforms play a vital role in the dissemination of health information. However, evidence suggests that a high proportion of Twitter posts (ie, tweets) are not necessarily accurate, and many studies suggest that tweets do not need to be accurate, or at least evidence based, to receive traction. This is a dangerous combination in the sphere of health information. OBJECTIVE: The first objective of this study is to examine health-related tweets originating from Saudi Arabia in terms of their accuracy. The second objective is to find factors that relate to the accuracy and dissemination of these tweets, thereby enabling the identification of ways to enhance the dissemination of accurate tweets. The initial findings from this study and methodological improvements will then be employed in a larger-scale study that will address these issues in more detail. METHODS: A health lexicon was used to extract health-related tweets using the Twitter application programming interface and the results were further filtered manually. A total of 300 tweets were each labeled by two medical doctors; the doctors agreed that 109 tweets were either accurate or inaccurate. Other measures were taken from these tweets’ metadata to see if there was any relationship between the measures and either the accuracy or the dissemination of the tweets. The entire range of this metadata was analyzed using Python, version 3.6.5 (Python Software Foundation), to answer the research questions posed. RESULTS: A total of 34 out of 109 tweets (31.2%) in the dataset used in this study were classified as untrustworthy health information. These came mainly from users with a non-health care background and social media accounts that had no corresponding physical (ie, organization) manifestation. Unsurprisingly, we found that traditionally trusted health sources were more likely to tweet accurate health information than other users. Likewise, these provisional results suggest that tweets posted in the morning are more trustworthy than tweets posted at night, possibly corresponding to official and casual posts, respectively. Our results also suggest that the crowd was quite good at identifying trustworthy information sources, as evidenced by the number of times a tweet’s author was tagged as favorited by the community. CONCLUSIONS: The results indicate some initially surprising factors that might correlate with the accuracy of tweets and their dissemination. For example, the time a tweet was posted correlated with its accuracy, which may reflect a difference between professional (ie, morning) and hobbyist (ie, evening) tweets. More surprisingly, tweets containing a kashida—a decorative element in Arabic writing used to justify the text within lines—were more likely to be disseminated through retweets. These findings will be further assessed using data analysis techniques on a much larger dataset in future work. JMIR Publications 2019-10-08 /pmc/articles/PMC6914129/ /pubmed/31596242 http://dx.doi.org/10.2196/14731 Text en ©Yahya Abdullah Albalawi, Nikola S Nikolov, Jim Buckley. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 08.10.2019. 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 http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Albalawi, Yahya
Nikolov, Nikola S
Buckley, Jim
Trustworthy Health-Related Tweets on Social Media in Saudi Arabia: Tweet Metadata Analysis
title Trustworthy Health-Related Tweets on Social Media in Saudi Arabia: Tweet Metadata Analysis
title_full Trustworthy Health-Related Tweets on Social Media in Saudi Arabia: Tweet Metadata Analysis
title_fullStr Trustworthy Health-Related Tweets on Social Media in Saudi Arabia: Tweet Metadata Analysis
title_full_unstemmed Trustworthy Health-Related Tweets on Social Media in Saudi Arabia: Tweet Metadata Analysis
title_short Trustworthy Health-Related Tweets on Social Media in Saudi Arabia: Tweet Metadata Analysis
title_sort trustworthy health-related tweets on social media in saudi arabia: tweet metadata analysis
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6914129/
https://www.ncbi.nlm.nih.gov/pubmed/31596242
http://dx.doi.org/10.2196/14731
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