{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["20(9)"],"submitter":["El Tantawi M"],"pubmed_abstract":["<h4>Background</h4>Increasing the reach of messages disseminated through Twitter promotes the success of Twitter-based health education campaigns.<h4>Objective</h4>This study aimed to identify factors associated with reach in a dental Twitter network (1) initially and (2) sustainably at individual and network levels.<h4>Methods</h4>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 re"],"journal":["Journal of medical Internet research"],"pagination":["e10781"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC6231799"],"repository":["biostudies-literature"],"pubmed_title":["Reach of Messages in a Dental Twitter Network: Cohort Study Examining User Popularity, Communication Pattern, and Network Structure."],"pmcid":["PMC6231799"],"pubmed_authors":["Aly NM","Fathy A","Mohamed AS","El Tantawi M","AlSubaie A","Al-Ansari A"],"additional_accession":[]},"is_claimable":false,"name":"Reach of Messages in a Dental Twitter Network: Cohort Study Examining User Popularity, Communication Pattern, and Network Structure.","description":"<h4>Background</h4>Increasing the reach of messages disseminated through Twitter promotes the success of Twitter-based health education campaigns.<h4>Objective</h4>This study aimed to identify factors associated with reach in a dental Twitter network (1) initially and (2) sustainably at individual and network levels.<h4>Methods</h4>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 re","dates":{"release":"2018-01-01T00:00:00Z","publication":"2018 Sep","modification":"2025-04-18T21:17:17.661Z","creation":"2019-10-19T07:07:19Z"},"accession":"S-EPMC6231799","cross_references":{"pubmed":["30213781"],"doi":["10.2196/10781"]}}