Engagement with health agencies on twitter.
Engagement with health agencies on twitter.
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DOI：
10.1371/journal.pone.0112235
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Polgreen P
中科院分区：
文献类型：
--
作者：
Bhattacharya S;Srinivasan P;Polgreen P
调查与美国联邦卫生机构通过Twitter参与相关的因素。我们的具体目标是研究与以下因素相关的因素：a）转发数量，B）机构推文和第一次转发之间的时间，以及c）机构推文和最后一次转发之间的时间。我们收集了来自25个联邦卫生机构及其130个账户的164，104条推文。我们使用负二项障碍回归模型和考克斯比例风险模型来探讨26个因素对代理敬业度的影响。帐户功能包括网络中心性、推文计数、好友数量、关注者和收藏夹。推文特征包括年龄、主题标签的使用、用户提及、URL、使用Sentistrength测量的情感以及由15个语义组表示的推文内容。三分之一的推文（53，556）没有转发。不到1%（613）的人转发超过100次（平均值= 284）。 障碍分析表明，主题标签，URL和用户提及与转发呈正相关;情绪与转发没有关联;推文计数与转发呈负相关。几乎所有的语义组，除了地理区域，职业和组织，正相关的转发。生存分析表明，参与度与推文年龄和追随者数量呈正相关。与更高水平的Twitter参与度相关的一些因素无法由机构改变，但其他因素可以修改（例如，使用hashtags、URL）。我们的研究结果为未来通过Twitter增加公共卫生参与的对照实验提供了背景。
To investigate factors associated with engagement of U.S. Federal Health Agencies via Twitter. Our specific goals are to study factors related to a) numbers of retweets, b) time between the agency tweet and first retweet and c) time between the agency tweet and last retweet. We collect 164,104 tweets from 25 Federal Health Agencies and their 130 accounts. We use negative binomial hurdle regression models and Cox proportional hazards models to explore the influence of 26 factors on agency engagement. Account features include network centrality, tweet count, numbers of friends, followers, and favorites. Tweet features include age, the use of hashtags, user-mentions, URLs, sentiment measured using Sentistrength, and tweet content represented by fifteen semantic groups. A third of the tweets (53,556) had zero retweets. Less than 1% (613) had more than 100 retweets (mean = 284). The hurdle analysis shows that hashtags, URLs and user-mentions are positively associated with retweets; sentiment has no association with retweets; and tweet count has a negative association with retweets. Almost all semantic groups, except for geographic areas, occupations and organizations, are positively associated with retweeting. The survival analyses indicate that engagement is positively associated with tweet age and the follower count. Some of the factors associated with higher levels of Twitter engagement cannot be changed by the agencies, but others can be modified (e.g., use of hashtags, URLs). Our findings provide the background for future controlled experiments to increase public health engagement via Twitter.
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影响因子：
3.7
作者：
Chew C;Eysenbach G
通讯作者：
Eysenbach G
DOI：
10.1093/bioinformatics/btr223
发表时间：
2011-07-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Bhattacharya S;Ha-Thuc V;Srinivasan P
通讯作者：
Srinivasan P
影响因子：
3.7
作者：
Dodds PS;Harris KD;Kloumann IM;Bliss CA;Danforth CM
通讯作者：
Danforth CM
DOI：
10.1145/2389707.2389713
发表时间：
2012-10-29
期刊：
SHB'12 : proceedings of the 2012 ACM International Workshop on Smart Health and Wellbeing : October 29, 2012, Maui, Hawaii, USA. International Workshop on Smart Health and Wellbeing (2012 : Maui, Hawaii)
影响因子：
--
作者：
Bian J;Topaloglu U;Yu F
通讯作者：
Yu F
影响因子：
6.4
作者：
Freifeld, Clark C.;Mandl, Kenneth D.;Ras, Ben Y.;Bronwnstein, John S.
通讯作者：
Bronwnstein, John S.