TY -的AU -王,道盟——Mentzakis Emmanouil AU -刺绣,马库斯AU - Ianni,安东内拉·PY - 2019 DA -·拉斯泰利2019/05/03 TI -估计的磨损在进食障碍的社区在Twitter上决定因素:一个工具变量方法乔- J地中海互联网Res SP - e10942六世- 21 - 5 KW -医学信息学KW -饮食失调KW -社会媒体KW -摩擦KW -情绪KW -社交网络KW -因果关系KW -辅助变量AB -背景:在受饮食失调(EDs)影响的人群中，使用社交媒体作为主要健康信息来源的人数稳步增加。研究已经调查了参与在线社区的个人的特征，然而关于参与中断和参与者退出这些社区的现象却知之甚少。目的:本研究旨在探讨饮食失调个体在Twitter上的辍学行为特征，并估计个人情绪和社交网络对辍学行为的因果影响。方法:采用滚雪球抽样方法，我们收集了一组在Twitter个人资料描述中自我认同为EDs的个体，以及他们的推文和社交网络，从208,063名用户中获得241,243,043条推文。使用自动情绪分析工具，通过推文中的语言使用来衡量个人的情绪，通过用户的关注网络来衡量网络中心性。在1.5年后(2016年2月11日至2017年8月17日)的随访期间观察用户的退出情况。使用线性回归和生存回归工具变量模型来估计情绪和网络中心性对辍学行为的影响。一个人的追随者(即被这个人追随的人)的平均属性水平被用作衡量这个人的属性的工具。结果:饮食失调的用户在Twitter上的活跃时间相对较短，我们的样本中有一半在账户创建6个月后退出。 Active users show more negative emotions and higher network centralities than dropped-out users. Active users tend to connect to other active users, whereas dropped-out users tend to cluster together. Estimation results suggest that users’ emotions and network centralities have causal effects on their dropout behaviors on Twitter. More specifically, users with positive emotions are more likely to drop out and have shorter lasting periods of activity online than users with negative emotions, whereas central users in a social network have longer lasting participation than peripheral users. Findings on users’ tweeting interests further show that users who attempt to recover from EDs are more likely to drop out than those who promote EDs as a lifestyle choice. Conclusions: Presence in online communities is strongly determined by the individual’s emotions and social networks, suggesting that studies analyzing and trying to draw condition and population characteristics through online health communities are likely to be biased. Future research needs to examine in more detail the links between individual characteristics and participation patterns if better understanding of the entire population is to be achieved. At the same time, such attrition dynamics need to be acknowledged and controlled when designing online interventions so as to accurately capture their intended populations. SN - 1438-8871 UR - //www.mybigtv.com/2019/5/e10942/ UR - https://doi.org/10.2196/10942 UR - http://www.ncbi.nlm.nih.gov/pubmed/31066718 DO - 10.2196/10942 ID - info:doi/10.2196/10942 ER -