热带地理 ›› 2020, Vol. 40 ›› Issue (3): 375-385.doi: 10.13284/j.cnki.rddl.003244
• ·“健康/医学地理视角下的新冠肺炎疫情解读”专题· • 上一篇 下一篇
收稿日期:
2020-03-20
修回日期:
2020-05-05
出版日期:
2020-05-31
发布日期:
2020-06-30
通讯作者:
田广增
E-mail:d06325002@ntu.edu.tw;1173931709@qq.com
作者简介:
孙宇婷(1993—),女,辽宁沈阳人,博士研究生,主要从事媒介地域形象研究,(E-mail)<email>d06325002@ntu.edu.tw</email>;
基金资助:
Sun Yuting1(), Xiao Fan1, Zhou Yong1, Tian Guangzeng2(
)
Received:
2020-03-20
Revised:
2020-05-05
Online:
2020-05-31
Published:
2020-06-30
Contact:
Tian Guangzeng
E-mail:d06325002@ntu.edu.tw;1173931709@qq.com
摘要:
公众关注作为疫情防控与舆情治理的重要环节,其时空差异与影响因素却鲜见被讨论。因此,文章将百度搜索指数作为网络公众关注度的测量指标,采用百度人口流动大数据和疫情实时监测数据,运用空间分析、时空可视化、回归分析等方法,分析2020-01-09—03-02中国公众对“新型冠状病毒”网络关注度的省域时空差异与影响因素。研究发现:1)在空间上,公众对疫情的关注度东、西部差异较大,沿海高于内陆,且与疫情高发区吻合;在时间上,武汉“封城”前后各省份的公众关注度分布格局基本趋于一致,且“封城”后均明显高于“封城”前;春节期间关注度达到最高峰,而后随疫情周期性规律(潜伏—暴发)呈波动式下降;关注主题遵循“从早期对相关病毒的搜索到后期关注临床诊断与发展状况”的疫情发展规律。2)疫情动态数据、武汉人口流动的日动态因素与固定区位特征的经济社会发展因素会不同程度地影响受众对疫情的关注度,当疫情基本得到控制,宏观区位因素对公众关注度的影响作用开始凸显,具有持续稳定的影响;3)影响因素在疫情暴发前后2个阶段对公众关注度起着不同的影响效果。在疫情暴发初期,公众更易受疫情动态信息影响引发主动搜索行为;而在疫情暴发后期阶段,公众将注意力转移到流入各省份的武汉人口上。
中图分类号:
孙宇婷, 肖凡, 周勇, 田广增. 新型冠状病毒肺炎疫情公众关注度的时空差异与影响因素[J]. 热带地理, 2020, 40(3): 375-385.
Sun Yuting, Xiao Fan, Zhou Yong, Tian Guangzeng. Spatial-Temporal Distribution and Influence Mechanism of Internet Public Attention on COVID-19: A Case Study on the Baidu Searching Index[J]. Tropical Geography, 2020, 40(3): 375-385.
表1
变量定义及描述性统计"
变量类型 | 变量来源 | 变量说明 | 均值 | 标准差 | 最小值 | 最大值 | |
---|---|---|---|---|---|---|---|
因变量 | 搜索指数 | 百度搜索指数 | 统计网民在百度网页搜索中对关键词的搜索频次/次 | 27 608.344 | 31 132.561 | 0 | 202 365 |
疫情 动态 资讯 | 确诊病例数 | nCov2019数据库 | 医学诊断判定为新冠肺炎的患者数量/例 | 226.581 | 330.560 | 0 | 1 350 |
死亡病例数 | 新冠肺炎的治愈出院患者数量/例 | 1.298 | 2.798 | 0 | 22 | ||
治愈病例数 | 新冠肺炎的死亡病例数量/例 | 92.500 | 194.388 | 0 | 1 206 | ||
人口 流动 因素 | 武汉迁出人口 | 百度迁徙数据 | 武汉迁出至该地区的人口数量占武汉迁出人口总量的比例/% | 0.537 | 0.083 | 0 | 0.646 |
迁入武汉人口 | 该地区迁入武汉的人口数量占武汉迁入人口总量的比例/% | 0.784 | 1.110 | 0 | 11.310 | ||
经济 社会 因素 | 人口规模 | 《2019年中国 统计年鉴》 | 各省常住人口数量/百万人 | 44.559 | 28.787 | 3.435 | 113.444 |
人均GDP | 人均地区生产总值/元 | 65 208.067 | 29 129.456 | 31 336 | 140 211 | ||
互联网普及率 | 《2018年网宿·中国 互联网发展报告》 | (全国各省市)网民数/人口数(%) | 56.230 | 8.830 | 43 | 80 |
表3
面板模型回归结果"
自变量 | 模型一 | 模型二 | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
第一阶段 | 第二阶段 | 第一阶段 | 第二阶段 | ||||||||
系数 | VIF | 系数 | VIF | 系数 | VIF | 系数 | VIF | ||||
类型 | 固定效应 | 固定效应 | 随机效应 | 混合效应 | |||||||
确诊病例数 | 1 430.740*** | 1.766 | -40.823*** | 3.624 | 1 906.676*** | 1.774 | -1.223 | 4.558 | |||
死亡病例数 | 30 403.490*** | 1.008 | -607.496* | 1.542 | 34 534.710*** | 1.028 | -903.835*** | 1.586 | |||
治愈病例数 | -822.525 | 1.742 | -43.334*** | 3.435 | -9 112.869 | 1.756 | -62.328*** | 3.525 | |||
武汉迁出人口 | -33 454.680*** | 1.509 | 9 655.013*** | 2.230 | -1 982.319** | 2.251 | 15 038.900*** | 2.300 | |||
迁入武汉人口 | -6 354.798*** | 1.552 | -599.438 | 2.414 | -1 364.255* | 3.016 | -1 725.092 | 2.625 | |||
人口规模 | — | — | — | — | 227.020*** | 2.360 | 910.535*** | 2.264 | |||
人均GDP | — | — | — | — | 0.124** | 4.126 | 0.157*** | 4.076 | |||
互联网普及率 | — | — | — | — | -267.195 | 4.936 | 436.656*** | 4.024 | |||
常数项 | — | — | — | — | 5 523.144* | — | -33 714.110*** | — | |||
样本量 | 480 | — | 1 140 | — | 480 | — | 1 140 | — | |||
R2 | 0.718 | — | 0.646 | — | 0.645 | — | 0.784 | — | |||
调整后 R2 | 0.696 | — | 0.635 | — | 0.639 | — | 0.782 | — | |||
F值 | 226.193*** | — | 403.713*** | — | 106.931*** | — | 512.992*** | — |
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