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首页> 外文期刊>Journal of medical Internet research >Reach of Messages in a Dental Twitter Network: Cohort Study Examining User Popularity, Communication Pattern, and Network Structure
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Reach of Messages in a Dental Twitter Network: Cohort Study Examining User Popularity, Communication Pattern, and Network Structure

机译:牙科Twitter网络中的消息范围:队列研究,研究用户受欢迎程度,通信模式和网络结构

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BackgroundIncreasing the reach of messages disseminated through Twitter promotes the success of Twitter-based health education campaigns.ObjectiveThis study aimed to identify factors associated with reach in a dental Twitter network (1) initially and (2) sustainably at individual and network levels.MethodsWe 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.ResultsAmong 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.ConclusionsReach 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.
机译:背景通过增加通过Twitter传播的消息的传播范围,可以促进基于Twitter的健康教育活动的成功。目的本研究旨在确定与牙科Twitter网络的传播范围相关的因素(1)最初和(2)在个人和网络级别上是可持续的。 2016-2017年来自沙特牙科学校的讲师和学生的Twitter用户名,并应用Gephi(社交网络分析工具)和社交媒体分析来计算用户和网络指标。进行内容分析以识别传播口腔健康信息的用户。研究结果达到基线并持续1.5年。解释变量是受欢迎程度(追随者,喜欢,被他人转发的推文数量),交流方式(推文,转发,回复,是否发布/转发口腔健康信息的数量)的指标。结果使用多对数回归模型研究关联性。结果在牙科用户中,基线时达到了31.8%,研究结束时达到了62.9%,总数达到749,923,最终下降到了37,169。在个人层面上,覆盖率与关注者人数(基线:优势比,OR = 1.003,95%CI = 1.001-1.005和可持续性:OR = 1.002,95%CI = 1.0001-1.003)相关,喜欢人数(基线: OR = 1.001、95%CI = 1.0001-1.002和可持续性:OR = 1.0031、95%CI = 1.0003-1.002)和答复(基线:OR = 1.02、95%CI = 1.005-1.04和可持续性:OR = 1.02, 95%CI = 1.004-1.03)。在网络级别,关注者,推文,转发和回复最少的用户具有最大的覆盖范围。在用户级别增加覆盖范围的因素在网络级别具有不同的影响。要扩大覆盖面,需要采取多种策略。

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