中国276个城市高校毕业生就业机会时空演变数据集（2005-2021年）

基于广泛收集的城市尺度的多源时空数据，我们从初次就业、生活舒适、环境宜人、社会融入、未来发展六个维度选取了31项指标全面构建了面向高校毕业生的，城市尺度的就业机会水平测度框架。基于基于投影寻踪模型实现就业机会水平的综合测度。基于不同机会的组合特征，使用SOFM神经网络识别了不同城市的机会地域类型及其演变过程。首次构建了面向中国高校毕业生长时序的城市就业选择的机会地图。同时，基于不同类型高校毕业生的异质性机会认知过程，识别了不同类别高校毕业生就业机会空间分布。Based on extensively collected multi-source spatiotemporal data at the urban scale, we comprehensively constructed an urban-scale employment opportunity level measurement framework targeting college graduates by selecting 31 indicators across six dimensions: initial employment, living comfort, pleasant environment, social integration, and future development. We implemented the comprehensive measurement of employment opportunity levels using the projection pursuit model. Based on the combined characteristics of different opportunity portfolios, we utilized the SOFM neural network to identify the regional opportunity types and their evolutionary trajectories across various cities. This study, for the first time, developed a long-time-series opportunity map for urban employment decisions of Chinese college graduates. Meanwhile, based on the heterogeneous opportunity cognition processes of different groups of college graduates, we identified the spatial distribution of employment opportunities for distinct categories of college graduates.