Detecting Ethnic Spatial Distribution of Business People Using Machine Learning

• Main Authors: Joomi Jun, Takayuki Mizuno
• Format: Article
• Language: English
• Published: MDPI AG 2020-04-01
• Series: Information
• Subjects: ethnicity classification; ethnic network; RNN; machine learning
• Online Access: https://www.mdpi.com/2078-2489/11/4/197
• ISSN: 2078-2489

The development of transportation and technology has spread human movements more quickly and widely. As a result, our societies are becoming more complex, composed of people of more diverse races, cultures, religions, and languages. In this study, we focus on the origins of ethnicity while analyzing the background of social members. To track the origin of the ethnicities of which a society is composed, we established a surname-nationality prediction model by learning from a Recurrent Neural Network (RNN) with data recorded by business peoples’ surnames and nationalities to predict nationality with high accuracy through surnames. This study is meaningful because it approaches the social scientific problems of ethnic composition within society through massive data and machine learning: the informatics approach.