Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak.
Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak.
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DOI：
10.1371/journal.pone.0014118
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发表时间：
2010-11-29
期刊：
影响因子：
3.7
通讯作者：
Eysenbach G
中科院分区：
文献类型：
--
作者：
Chew C;Eysenbach G
调查是衡量公众对紧急情况的看法的常用方法，但可能成本高，耗时长。我们建议并评估了一个互补的“infoveplayer”的方法，在2009年H1N1流感大流行期间使用Twitter。我们的研究旨在：1）监控“H1N1”与“猪流感”这两个术语的使用情况; 2）对“推文”进行内容分析; 3）验证Twitter作为实时内容、情绪和公众关注趋势跟踪工具的有效性。在2009年5月1日至12月31日期间，我们存档了超过200万条包含关键词“猪流感”、“猪流感”和/或“H1N1”的Twitter帖子。使用Infovigil，一个信息监视系统。使用“H1N1”的推文从8.8%增加到40.5%（R2 = 0.788; p<0.001），表明逐渐采用世界卫生组织推荐的术语。 从9天，4周的间隔中随机选择了5，395条推文，并使用三轴编码方案进行编码。为了跟踪推文内容并测试自动编码的可行性，我们创建了关键字的数据库查询，并将这些结果与手动编码相关联。内容分析显示，与资源相关的帖子最常被分享（52.6%）。4.5%的病例被确定为错误信息。新闻网站是最受欢迎的来源（23.2%），而政府和卫生机构只有1.5%的时间被链接。7/10例自动查询与手动编码相关。几个Twitter活动高峰与重大新闻报道相吻合。我们的研究结果与H1N1发病率数据相关性良好。这项研究说明了利用社交媒体进行公共卫生“信息学”研究的潜力。2009年H1N1相关推文主要用于传播来自可靠来源的信息，但也是意见和经验的来源。推文可用于实时内容分析和知识翻译研究，使卫生当局能够回应公众的关切。
Surveys are popular methods to measure public perceptions in emergencies but can be costly and time consuming. We suggest and evaluate a complementary “infoveillance” approach using Twitter during the 2009 H1N1 pandemic. Our study aimed to: 1) monitor the use of the terms “H1N1” versus “swine flu” over time; 2) conduct a content analysis of “tweets”; and 3) validate Twitter as a real-time content, sentiment, and public attention trend-tracking tool. Between May 1 and December 31, 2009, we archived over 2 million Twitter posts containing keywords “swine flu,” “swineflu,” and/or “H1N1.” using Infovigil, an infoveillance system. Tweets using “H1N1” increased from 8.8% to 40.5% (R 2 = .788; p<.001), indicating a gradual adoption of World Health Organization-recommended terminology. 5,395 tweets were randomly selected from 9 days, 4 weeks apart and coded using a tri-axial coding scheme. To track tweet content and to test the feasibility of automated coding, we created database queries for keywords and correlated these results with manual coding. Content analysis indicated resource-related posts were most commonly shared (52.6%). 4.5% of cases were identified as misinformation. News websites were the most popular sources (23.2%), while government and health agencies were linked only 1.5% of the time. 7/10 automated queries correlated with manual coding. Several Twitter activity peaks coincided with major news stories. Our results correlated well with H1N1 incidence data. This study illustrates the potential of using social media to conduct “infodemiology” studies for public health. 2009 H1N1-related tweets were primarily used to disseminate information from credible sources, but were also a source of opinions and experiences. Tweets can be used for real-time content analysis and knowledge translation research, allowing health authorities to respond to public concerns.
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影响因子：
3.7
作者：
Jones JH;Salathé M
通讯作者：
Salathé M
沙特公众对猪流感大流行的认识、态度和做法。
影响因子：
3.7
作者：
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通讯作者：
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影响因子：
105.7
作者：
Eysenbach, G;Köhler, C
通讯作者：
Köhler, C
影响因子：
28.2
作者：
Lau, Joseph T. F.;Griffiths, Sian;Tsui, Hi Yi
通讯作者：
Tsui, Hi Yi
影响因子：
4.4
作者：
Blendon, RJ;Benson, JM;Weldon, KJ
通讯作者：
Weldon, KJ