{"title":"Social Network Analysis of Real Estate Transactions in Korea","authors":"Seung Chul Noh","doi":"10.24957/hsr.2024.32.1.5","DOIUrl":null,"url":null,"abstract":"This study analyzes the characteristics of real estate transactions from 2017 to 2022, distinguishing between transactions within the region(si, gun, gu), adjacent regions, and non-adjacent regions. It uses social network analysis methods to derive the characteristics of the network and the actors (si. gun, gu). The research results show that about 50~55% of the collective building transactions occur within the region, about 15% between adjacent regions, and about 30% between non-adjacent regions. As a result of analyzing transactions between non-adjacent regions through a network approach, most regions belong to one real estate transaction network centered on the metropolitan area, and many regions can influence each other in real estate transactions. The significance of this study lies in presenting a new approach to real estate transactions by analyzing real estate transactions between cities and counties in Korea through a social network approach, and deriving policy implications through this.","PeriodicalId":255849,"journal":{"name":"Korean Association for Housing Policy Studies","volume":"25 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Korean Association for Housing Policy Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24957/hsr.2024.32.1.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study analyzes the characteristics of real estate transactions from 2017 to 2022, distinguishing between transactions within the region(si, gun, gu), adjacent regions, and non-adjacent regions. It uses social network analysis methods to derive the characteristics of the network and the actors (si. gun, gu). The research results show that about 50~55% of the collective building transactions occur within the region, about 15% between adjacent regions, and about 30% between non-adjacent regions. As a result of analyzing transactions between non-adjacent regions through a network approach, most regions belong to one real estate transaction network centered on the metropolitan area, and many regions can influence each other in real estate transactions. The significance of this study lies in presenting a new approach to real estate transactions by analyzing real estate transactions between cities and counties in Korea through a social network approach, and deriving policy implications through this.