基于社交媒体大数据的禽流感社会认知构建

Yuejiao Wang, Zhidong Cao
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引用次数: 0

摘要

在禽流感高发期间,主流媒体和社交媒体大量报道疫情,动员民众防控禽流感。本文从新闻、论坛、app、微信、微博等渠道收集禽流感相关报道,形成5个数据集。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。我们还利用MDS方法将议程设置差异矩阵投影到二维空间中形成认知地图,分析媒体平台相对于新闻的认知漂移。结果表明,app与新闻的议程设置网络相关系数最高,为0.9193,微博与新闻的相关系数最低,为0.5611。app、论坛和微信的认知地图相对于新闻的认知地图有轻微的平移和旋转。但它们在议程设置中的相对位置关系与新闻类似,微博除外。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Social Cognition Construction of the Avian Flu based on Social Media Big Data
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.
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