Properties analysis of refugee populations around the world: A visibility graph network approach.

The refugee problem is one of the most important issues facing the international community today. It not only troubles the countries where refugees are generated but also has a great impact on the countries where refugees are influx. With the continuous development of globalization, the refugee problem is no longer a problem of a country or a region, but a global problem faced by the international community. To cope with the global refugee problem, this paper analyzes the number of refugees in 156 countries from 1990 to 2020 and transforms the refugee population data of these countries into a complex network through a time series visibility graph (VG) method. First, we categorize the income level of 156 countries and analyze the impact of income level on the increase of refugee numbers. Then, the evaluation index of the number of refugees is obtained through the VG method. Finally, a TOPSIS comprehensive evaluation method based on the entropy weight approach is employed to analyze the data. This paper includes two main contributions. First, the application of the VG method provides a new perspective for enriching the modeling of the global refugee population growth trend. Second, this paper shows that the TOPSIS evaluation method based on the entropy weight method is effective, which provides a new method for further research on the global refugee population growth trend. [ABSTRACT FROM AUTHOR]