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Measuring interaction among cities in China: A geographical awareness approach with social media data

机译:衡量中国城市的互动:社交媒体数据的地理意识方法

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Unlike the large body of research on investigating interactions among cities using survey data, the social media-based city interaction study has received much less exploration. Based on geographical studies of social media content in China, we develop a few indices quantifying various levels of geographical awareness among cities. (1) We find that the geographical awareness proxy by the social media-based indices can measure interactions among cities. Specifically, the geographical awareness among cities follows gravitational law and is highly correlated with mobility flows. (2) The spatial in-awareness index (SIAI) is an appropriate index indicating a city's ranking in the urban hierarchy (3) the spatial out-awareness rate (SOAR) can indicate the interactions from a focal city to other cities. Our findings also show that SOAR can predict the number of people infected during a pandemic in a city system. Once the origin city or hotspots of the outbreak and the number of infected persons within those cities are known, we can use the social media-based SOAR index to predict number of cases for other else cities in the urban system. With this information, governments can properly and efficiently deliver medical equipment and staff to cities where large populations are infected.
机译:与使用调查数据调查城市之间的互动的大型研究,社会媒体的城市互动研究得到了更少的探索。基于中国社会媒体内容的地理研究,我们开发了一些规范,量化城市之间各种地理意识的指标。 (1)我们发现社交媒体的索引的地理意识代理可以衡量城市之间的互动。具体而言,城市之间的地理意识遵循引力法,与移动性高度相关。 (2)空间入学度指数(SIAI)是一个适当指数,表明城市等级中的城市排名(3)空间出版率(SOAR)可以表明焦点城与其他城市的互动。我们的研究结果还表明飙升可以预测城市系统的大流行期间感染的人数。一旦爆发的原始城市或热点以及这些城市内的受感染者的数量,我们就可以使用基于社交媒体的SOAR指数来预测城市系统中其他城市的案件数量。通过这些信息,各国政府可以妥善,有效地将医疗设备和员工提供给大众人群的城市。

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