Representative Methods of Computational Socioeconomics
Physics and Society
2021-09-09 v2
Abstract
The increasing data availability and imported analyzing tools from computer science and physical science have sharply changed traditional methodologies of social sciences, leading to a new branch named computational socioeconomics that studies various phenomena in socioeconomic development by using quantitative methods based on large-scale real-world data. Sited on recent publications, this Perspective will introduce three representative methods: (i) natural data analyses, (ii) large-scale online experiments, and (iii) integration of big data and surveys. This Perspective ends up with in-depth discussion on the limitations and challenges of the above-mentioned emerging methods.
Cite
@article{arxiv.2105.09213,
title = {Representative Methods of Computational Socioeconomics},
author = {Tao Zhou},
journal= {arXiv preprint arXiv:2105.09213},
year = {2021}
}
Comments
7 pages, without figures or tables