Econoinformatics meets Data-Centric Social Sciences

TL;DR

This paper discusses how econoinformatics leverages large-scale, multi-source spatio-temporal data to analyze complex socio-economic systems, with applications to financial markets and travel data.

Contribution

It introduces methods for managing data complexity and integrating diverse data sources, emphasizing the importance of spatio-temporal information in social sciences.

Findings

Spatio-temporal data is crucial for synthesizing diverse socio-economic data.

Applications include analysis of stock exchanges, foreign exchange, and travel bookings.

Methods for linking and treating large, complex datasets are discussed.

Abstract

Our society has been computerised and globalised due to emergence and spread of information and communication technology (ICT). This enables us to investigate our own socio-economic systems based on large amounts of data on human activities. In this article, methods of treating complexity arising from a vast amount of data, and linking data from different sources, are discussed. Furthermore, several examples are given of studies into the applications of econoinformatics for the Japanese stock exchange, foreign exchange markets, domestic hotel booking data and international flight booking data are shown. It is the main message that spatio-temporal information is a key element to synthesise data from different data sources.