a Bob Schieffer College of Communication , Texas Christian University , Fort Worth , TX , USA.
b Perelman School of Medicine , University of Pennsylvania , Philadelphia , PA , USA.
J Health Commun. 2018;23(12):1026-1035. doi: 10.1080/10810730.2018.1540671. Epub 2018 Nov 7.
Twitter is one of the largest social networking sites (SNSs) in the world, yet little is known about what cardiovascular health related tweets go viral and what characteristics are associated with retransmission. The current study aims to identify a function of the observable characteristics of cardiovascular tweets, including characteristics of the source, content, and style that predict the retransmission of these tweets. We identified a random sample of 1,251 tweets associated with CVD originating from the United States between 2009 and 2015. Automated coding was conducted on the affect values of the tweets as well as the presence/absence of any URL, mention of another user, question mark, exclamation mark, and hashtag. We hand-coded the tweets' novelty, utility, theme, and source. The count of retweets was positively predicted by message utility, health organization source, and mention of user handle, but negatively predicted by the presence of URL and nonhealth organization source. Regarding theme, compared to the tweets focusing on risk factor, tweets on treatment and management predicted fewer retweets while supportive tweets predicted more retweets. These findings suggest opportunities for harnessing Twitter to better disseminate cardiovascular educational and supportive information on SNSs.
推特是世界上最大的社交媒体网站之一,但对于哪些与心血管健康相关的推文会传播开来,以及哪些特征与转发有关,人们知之甚少。本研究旨在确定可观察到的心血管推文特征的一个功能,包括来源、内容和风格特征,这些特征可以预测这些推文的转发。我们从 2009 年至 2015 年期间从美国确定了一个与 CVD 相关的 1251 条随机推特样本。对推特的情感价值以及是否存在 URL、提及其他用户、问号、感叹号和话题标签进行了自动编码。我们对手写编码的推文新颖性、实用性、主题和来源进行了编码。转发的数量与信息的实用性、健康组织来源以及用户的提及呈正相关,但与 URL 的存在和非健康组织来源呈负相关。就主题而言,与关注风险因素的推文相比,关于治疗和管理的推文的转发量较少,而支持性推文的转发量较多。这些发现表明,有机会利用推特在社交媒体上更好地传播心血管教育和支持性信息。