Investigating the distribution of university alumni populations within South Korea and Taiwan based on data from the LinkedIn advertising platform

被引:2
|
作者
Heo, Nayoung [1 ]
Chang, Hsin-Chieh [2 ]
Abel, Guy J. [1 ,3 ]
机构
[1] Shanghai Univ, Asian Demog Res Inst, Sch Sociol & Polit Sci, Shanghai, Peoples R China
[2] Fudan Univ, Sch Social Dev & Publ Policy, Dept Sociol, Shanghai, Peoples R China
[3] Univ Vienna, Int Inst Appl Syst Anal, Wittgenstein Ctr, IIASA,OeAW, Laxenburg, Austria
关键词
Alumni network; Spatial redistribution; Universities; Social media; LinkedIn advertising platform; INTERNAL MIGRATION; COLLEGE; FLOWS;
D O I
10.1016/j.cities.2023.104315
中图分类号
TU98 [区域规划、城乡规划];
学科分类号
0814 ; 082803 ; 0833 ;
摘要
Universities produce, retain and attract high-skilled individuals and promote economic growth in their cities and surrounding areas. One of the main contributing factors to the impact of universities on local development is the size of alumni that remain after graduation. In recent years, new data sources have emerged from social media that can potentially provide more timely and unique estimates of population redistribution. We use LinkedIn advertising platform data to measure alumni population distributions in South Korea and Taiwan. In both countries, there are decreasing numbers of students entering universities, with potential negative impacts on local development. We validated the LinkedIn data using external comparisons of totals against official data on the distribution of tertiary-educated populations and university student population sizes. We use multi-level gravity models to compare and contrast the spatial distributions of the alumni networks in the two countries, and the related push and pull factors. The data from LinkedIn provide plausible measures of alumni networks and an insight into the potential drivers of alumni population distributions. The results provide useful guidance on the potential impacts when reorganizing university systems in the coming decades.
引用
收藏
页数:12
相关论文
empty
未找到相关数据