Representative Methods of Computational Socioeconomics

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.

7 pages, without figures or tables

References in corpus (3)

• No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World
• Computational Socioeconomics
• Predicting Academic Performance for College Students: A Campus Behavior Perspective