Computational socioeconomics
-
Gao, Jian
CompleX Lab, University of Electronic Science and Technology of China, Chengdu, PR China - MIT Media Lab, Massachusetts Institute of Technology, Cambridge, USA - Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China
-
Zhang, Yi-Cheng
Institute of Fundamental and Frontier Science, University of Electronic Science and Technology of China, Chengdu, China - Department of Physics, University of Fribourg, Switzerland
-
Zhou, Tao
CompleX Lab, University of Electronic Science and Technology of China, Chengdu, PR China - Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China - Institution of New Economic Development, Chengdu, China
Published in:
- Physics Reports. - 2019, vol. 817, p. 1–104
English
Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development. The understanding of socioeconomic processes provides foundations to quantify global economic development, to map regional industrial structure, and to infer individual socioeconomic status. In this review, we will make a brief manifesto about a new interdisciplinary research field named Computational Socioeconomics, followed by detailed introduction about data resources, computational tools, data-driven methods, theoretical models and novel applications at multiple resolutions, including the quantification of global economic inequality and complexity, the map of regional industrial structure and urban perception, the estimation of individual socioeconomic status and demographic, and the real-time monitoring of emergent events. This review, together with pioneering works we have highlighted, will draw increasing interdisciplinary attentions and induce a methodological shift in future socioeconomic studies.
-
Faculty
- Faculté des sciences et de médecine
-
Department
- Département de Physique
-
Language
-
-
Classification
-
Economics
-
License
-
License undefined
-
Identifiers
-
-
Persistent URL
-
https://folia.unifr.ch/unifr/documents/308232
Statistics
Document views: 61
File downloads: