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Reach of Messages in a Dental Twitter Network: Cohort Study Examining User Popularity, Communication Pattern, and Network Structure

BACKGROUND: Increasing the reach of messages disseminated through Twitter promotes the success of Twitter-based health education campaigns. OBJECTIVE: This study aimed to identify factors associated with reach in a dental Twitter network (1) initially and (2) sustainably at individual and network le...

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Autores principales: El Tantawi, Maha, Al-Ansari, Asim, AlSubaie, Abdulelah, Fathy, Amr, Aly, Nourhan M, Mohamed, Amira S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6231799/
https://www.ncbi.nlm.nih.gov/pubmed/30213781
http://dx.doi.org/10.2196/10781
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author El Tantawi, Maha
Al-Ansari, Asim
AlSubaie, Abdulelah
Fathy, Amr
Aly, Nourhan M
Mohamed, Amira S
author_facet El Tantawi, Maha
Al-Ansari, Asim
AlSubaie, Abdulelah
Fathy, Amr
Aly, Nourhan M
Mohamed, Amira S
author_sort El Tantawi, Maha
collection PubMed
description BACKGROUND: Increasing the reach of messages disseminated through Twitter promotes the success of Twitter-based health education campaigns. OBJECTIVE: This study aimed to identify factors associated with reach in a dental Twitter network (1) initially and (2) sustainably at individual and network levels. METHODS: We used instructors’ and students’ Twitter usernames from a Saudi dental school in 2016-2017 and applied Gephi (a social network analysis tool) and social media analytics to calculate user and network metrics. Content analysis was performed to identify users disseminating oral health information. The study outcomes were reach at baseline and sustainably over 1.5 years. The explanatory variables were indicators of popularity (number of followers, likes, tweets retweeted by others), communication pattern (number of tweets, retweets, replies, tweeting/ retweeting oral health information or not). Multiple logistic regression models were used to investigate associations. RESULTS: Among dental users, 31.8% had reach at baseline and 62.9% at the end of the study, reaching a total of 749,923 and dropping to 37,169 users at the end. At an individual level, reach was associated with the number of followers (baseline: odds ratio, OR=1.003, 95% CI=1.001-1.005 and sustainability: OR=1.002, 95% CI=1.0001-1.003), likes (baseline: OR=1.001, 95% CI=1.0001-1.002 and sustainability: OR=1.0031, 95% CI=1.0003-1.002), and replies (baseline: OR=1.02, 95% CI=1.005-1.04 and sustainability: OR=1.02, 95% CI=1.004-1.03). At the network level, users with the least followers, tweets, retweets, and replies had the greatest reach. CONCLUSIONS: Reach was reduced by time. Factors increasing reach at the user level had different impact at the network level. More than one strategy is needed to maximize reach.
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spelling pubmed-62317992018-12-03 Reach of Messages in a Dental Twitter Network: Cohort Study Examining User Popularity, Communication Pattern, and Network Structure El Tantawi, Maha Al-Ansari, Asim AlSubaie, Abdulelah Fathy, Amr Aly, Nourhan M Mohamed, Amira S J Med Internet Res Original Paper BACKGROUND: Increasing the reach of messages disseminated through Twitter promotes the success of Twitter-based health education campaigns. OBJECTIVE: This study aimed to identify factors associated with reach in a dental Twitter network (1) initially and (2) sustainably at individual and network levels. METHODS: We used instructors’ and students’ Twitter usernames from a Saudi dental school in 2016-2017 and applied Gephi (a social network analysis tool) and social media analytics to calculate user and network metrics. Content analysis was performed to identify users disseminating oral health information. The study outcomes were reach at baseline and sustainably over 1.5 years. The explanatory variables were indicators of popularity (number of followers, likes, tweets retweeted by others), communication pattern (number of tweets, retweets, replies, tweeting/ retweeting oral health information or not). Multiple logistic regression models were used to investigate associations. RESULTS: Among dental users, 31.8% had reach at baseline and 62.9% at the end of the study, reaching a total of 749,923 and dropping to 37,169 users at the end. At an individual level, reach was associated with the number of followers (baseline: odds ratio, OR=1.003, 95% CI=1.001-1.005 and sustainability: OR=1.002, 95% CI=1.0001-1.003), likes (baseline: OR=1.001, 95% CI=1.0001-1.002 and sustainability: OR=1.0031, 95% CI=1.0003-1.002), and replies (baseline: OR=1.02, 95% CI=1.005-1.04 and sustainability: OR=1.02, 95% CI=1.004-1.03). At the network level, users with the least followers, tweets, retweets, and replies had the greatest reach. CONCLUSIONS: Reach was reduced by time. Factors increasing reach at the user level had different impact at the network level. More than one strategy is needed to maximize reach. JMIR Publications 2018-09-13 /pmc/articles/PMC6231799/ /pubmed/30213781 http://dx.doi.org/10.2196/10781 Text en ©Maha El Tantawi, Asim Al-Ansari, Abdulelah AlSubaie, Amr Fathy, Nourhan M Aly, Amira S Mohamed. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 13.09.2018. 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
El Tantawi, Maha
Al-Ansari, Asim
AlSubaie, Abdulelah
Fathy, Amr
Aly, Nourhan M
Mohamed, Amira S
Reach of Messages in a Dental Twitter Network: Cohort Study Examining User Popularity, Communication Pattern, and Network Structure
title Reach of Messages in a Dental Twitter Network: Cohort Study Examining User Popularity, Communication Pattern, and Network Structure
title_full Reach of Messages in a Dental Twitter Network: Cohort Study Examining User Popularity, Communication Pattern, and Network Structure
title_fullStr Reach of Messages in a Dental Twitter Network: Cohort Study Examining User Popularity, Communication Pattern, and Network Structure
title_full_unstemmed Reach of Messages in a Dental Twitter Network: Cohort Study Examining User Popularity, Communication Pattern, and Network Structure
title_short Reach of Messages in a Dental Twitter Network: Cohort Study Examining User Popularity, Communication Pattern, and Network Structure
title_sort reach of messages in a dental twitter network: cohort study examining user popularity, communication pattern, and network structure
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6231799/
https://www.ncbi.nlm.nih.gov/pubmed/30213781
http://dx.doi.org/10.2196/10781
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