Big Data Analysis on Global Community Formation and Isolation

In this book, the authors analyze big data on global interdependence caused by the flows of commodities, money, and people, using a network science approach to obtain differing views of globalization and to clarify the facts on isolation of communities.

Globalization reduces international economic inequality, i.e., it allows emerging countries to catch up while it increases relative poverty in some advanced countries. How should this trade-off between international and domestic inequalities be resolved? At the same time, the reduction of biocultural diversity caused by globalization needs to be avoided. What kind of change is required in local communities to conserve biocultural diversity?

On the issue of commodity flow, research results of the supply-chain network, isolation in industry, and resource flows and stocks are presented in this book. For monetary flow, ownership networks, value-added networks, and profit shifting were studied; and regarding the flow of people, linkage of ethnic groups, immigrant assimilation, and refugees were examined. Based on the resulting view of globalization and isolation, the development of the isolation index using machine learning is discussed. Finally, recommendations for evidence-based policymaking in the United Nations are considered.

• Supply Chain Network
• Ownership Network
• Value Added Network
• Traditional Industry
• Profit Shifting
• Digital Economy
• Ethnic Group
• Immigrant Assimilation
• Refugees
• Policy Recommendation
• Evidence-Based Policy Making
• Big Data
• Community Analysis
• Network Science
• Data Science

• Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, Kyoto, Japan

  Yuichi Ikeda

• Department of Mathematics, Niigata University, Niigata, Nishi-ku, Japan

  Hiroshi Iyetomi

• National Institute of Informatics, Tokyo, Japan

  Takayuki Mizuno

Policies and ethics