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Social Cognition Construction of the Avian Flu based on Social Media Big Data

机译:基于社交媒体大数据的禽流感的社会认知构建

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During the high incidence of avian flu, the mainstream media and social media report a lot on the epidemic, mobilizing the people to prevent and control avian flu. This paper collects reports on avian flu from News, Forums, Apps, WeChat and Microblog and forms five data sets. We extract agenda-settings from the News dataset and build agenda-setting networks of the five datasets. Then we use the QAP test to verify the relevance of these agenda-setting networks. We also project the agenda-setting dissimilarity matrices into a two-dimensional space using the MDS method to form cognitive maps, analyzing the cognitive drift of media platforms relative to News. Results show that the agenda-setting networks of Apps and News have the highest correlation coefficient of 0.9193, while Microblog and News have the lowest correlation coefficient of 0.5611. The cognitive maps of Apps, Forum and WeChat have a slight translation and rotation relative to the cognitive map of News. But their relative positional relationship among agenda-settings are similar with News, expect Microblog.
机译:在禽流感的高发病率期间,主流媒体和社会媒体报告了很多流行病,动员人民预防和控制禽流感。本文从新闻,论坛,应用程序,微博和微博以及五个数据集中收集有关禽流感的报告。我们从新闻数据集中提取议程 - 设置并构建五个数据集的议程设置网络。然后我们使用QAP测试来验证这些议程设置网络的相关性。我们还使用MDS方法将议程 - 将不同的矩阵投影到二维空间中,以形成认知地图,分析媒体平台相对于新闻的认知漂移。结果表明,应用和新闻议程设定网络具有0.9193的最高相关系数,而微博和新闻具有0.5611的最低相关系数。应用程序,论坛和微信的认知地图相对于新闻的认知地图具有轻微的翻译和旋转。但是,他们的相对位置关系与议程 - 设置相似,预计微博。

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