基于招聘大数据的无锡市就业空间特征分析
Analysis of the Employment Spatial Characteristics of Wuxi City Based on the Big Data from 51job.com
DOI: 10.12677/CSA.2022.121017, PDF,    国家自然科学基金支持
作者: 饶加旺：江苏省测绘工程院江苏时空大数据建设中心，江苏 南京;中国科学院南京地理与湖泊研究所，江苏 南京；周秀华：江苏省测绘工程院江苏时空大数据建设中心，江苏 南京 ；马荣华*：中国科学院南京地理与湖泊研究所，江苏 南京
关键词: 新冠肺炎疫情；就业空间特征；差异性；招聘网；无锡市；Moran’s I指数；COVID-19； Spatial Characteristics of Employment； The Differences； 51job.com； Wuxi City； Moran’s I
摘要: 为揭示“新冠疫情”对招聘就业的影响，基于网络爬虫方法，快速获取了2019年2~4月、2020年2~4月“新冠疫情”前后无锡市各行业发布的招聘大数据，运用统计分析、核密度分析、空间自相关分析法，分析了疫情前后无锡市就业需求和空间分布变化特征。结果表明：疫情严重影响无锡市的就业，尤其对服务业、会计/金融业冲击最大；招聘需求总体呈现“一团两核”的空间分布，疫情后有往东部城镇转移的趋势；各行业的全局Moran’s I指数均为正值，表明无锡市招聘就业需求存在显著的空间聚集性；高–高型聚集区分布于无锡市主城区、低–低型聚集区主要分布在宜兴市，疫情后两者均呈增加的趋势。从就业需求的角度为复工复产和优化产业布局提供有效的数据基础和决策支持。
Abstract: In order to explore the effect of COVID-19 on recruitment jobs, data of February to April 2019 and February to April 2020 from 51job.com of Wuxi city were quickly obtained by web crawl which contained 11 industries. Employment demand change and spatial distribution characteristics were analyzed by statistical analysis, kernel density, and spatial auto-correlation analysis methods. Results showed that: there was bigger negative impact by COVID-19 on Wuxi city labor market, especially for service and accounting/finance; recruitment demand of this city presented a mass of two cores spatial distribution and high demand was shifted to eastern part of Wuxi after COVID-19; the global Moran’s I of all industries before and after outbreak of COVID-19 were all positive indicated significant spatial clustering of recruitment demand; H-H cluster type of recruitment demand mainly distributed in the center of Wuxi city; and L-L cluster type mainly concentrated in Yixing; both were increased after COVID-19. From the perspective of the employment demand, this paper provided effective data base and decision support to return to work and production, and optimize the industrial layout.
文章引用：饶加旺, 周秀华, 周松, 马荣华. 基于招聘大数据的无锡市就业空间特征分析[J]. 计算机科学与应用, 2022, 12(1): 158-168. https://doi.org/10.12677/CSA.2022.121017

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