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K-Means Clustering 알고리즘과 헤도닉 모형을 활용한 서울시 연립 · 다세대 군집분류 방법에 관한 연구
권순재(Soonjae Kwon),김성현(Seonghyeon Kim),탁온식(Onsik Tak),정현희(Hyeonhee Jeong) 한국지능정보시스템학회 2017 지능정보연구 Vol.23 No.3
최근 도심을 중심으로 연립 · 다세대의 거래가 활성화되고 직방, 다방등과 같은 플랫폼 서비스가 성장하고 있다. 연립 · 다세대는 수요 변화에 따른 시장 규모 확대와 함께 정보 비대칭으로 인해 사회적 문제가 발생 되는 등 부동산 정보의 사각지대이다. 또한, 서울특별시 또는 한국감정원에서 사용하는 5개 또는 25개의 권역 구분은 행정구역 내부를 중심으로 설정되었으며, 기존의 부동산 연구에서 사용되어 왔다. 이는 도시계획에 의한 권역구분이기 때문에 부동산 연구를 위한 권역 구분이 아니다. 이에 본 연구에서는 기존 연구를 토대로 향후 주택가격추정에 있어 서울특별시의 공간구조를 재설정할 필요가 있다고 보았다. 이에 본 연구에서는 연립 · 다세대 실거래가 데이터를 기초로 하여 헤도닉 모형에 적용하였으며, 이를 K-Means Clustering 알고리즘을 사용해 서울특별시의 공간구조를 다시 군집하였다. 본 연구에서는 2014년 1월부터 2016년 12월까지 3년간 국토교통부의 서울시 연립 · 다세대 실거래가 데이터와 2016년 공시지가를 활용하였다. 실거래가 데이터에서 본 연구에서는 지하거래제거, 면적당 가격 표준화 및 5이상 -5이하의 실거래 사례 제거와 같이 데이터 제거를 통한 데이터 전처리 작업을 수행하였다. 데이터전처리 후 고정된 초기값 설정으로 결정된 중심점이 매번 같은 결과로 나오게 K-means Clustering을 수행한 후 군집 별로 헤도닉 모형을 활용한 회귀분석을 하였으며, 코사인 유사도를 계산하여 유사성 분석을 진행하였다. 이에 본 연구의 결과는 모형 적합도가 평균 75% 이상으로, 헤도닉 모형에 사용된 변수는 유의미하였다. 즉, 기존 서울을 행정구역 25개 또는 5개의 권역으로 나뉘어 실거래가지수 등 부동산 가격 관련 통계지표를 작성하던 방식을 속성의 영향력이 유사한 영역을 묶어 16개의 구역으로 나누었다. 따라서 본 연구에서는 K-Means Clustering 알고리즘에 실거래가 데이터로 헤도닉 모형을 활용하여 연립․다세대 실거래가를 기반으로 한 군집분류방법을 도출하였다. 또한, 학문적 실무적 시사점을 제시하였고, 본 연구의 한계점과 향후 연구 방향에 대해 제시하였다. Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government"s spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper researc
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뉴스진위 및 인지욕구에 따른 정보수용자의 수용(이해)과 확산영향에 대한 탐색적 연구
조아라,권순재,Cho, Ara,Kwon, Soonjae 한국지식경영학회 2019 지식경영연구 Vol.20 No.2
The purpose of this study was to explore the factors influencing acceptance (e.g., comprehension,) and diffusion of information recipients' by depending on the authenticity of news. Specifically, this study has examined the effects of the news contents(political vs. general), need for cognition(high vs. low) and authenticity of the News(real news vs. fake news) on both acceptance and diffusion of news. Based on previous work, this study has developed a conceptual model to present each research hypothesis and tested it by conducting experiments as the follows. As a result, according to the authenticity of the news and the contents of the news (political and general), the acceptance of political contents was high regardless of the authenticity of the news, and the acceptance of real news was higher than that of fake news. However, in the proliferation (comment), both the political contents and the general contents showed the characteristic of spreading (commenting) fake news rather than real news. contrary to this, the cognitive level did not show any significant difference in acceptance (understanding) and proliferation (comment, sharing, recommendation). This study provides academic implications in that it examines the influences of accepting (comprehension) and diffusion (comment, sharing, recommendation) of real news and fake news. It also provides practical implications for responding to fake news and new marketing strategies in an environment where contents are delivered through diverse social media.
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안창민 ( Changmin Ahn ),권순재 ( Soonjae Kwon ),정현희 ( Hyeonhee Jeong ) 한국지식경영학회 2018 지식경영연구 Vol.19 No.1
While there are lots of studies on examining the effects of social rapport in many research areas, however, there is a little work in examining the effect of the social rapport in social network service (SNS) contexts. Thus, this study attempts to examine the effect of social rapport in SNS settings. To address the research questions, this study has presented its hypotheses and conducted three experimental approaches by collecting 180 data from student subjects who have prior experiences on using SNSs to verify the hypotheses. This study has examined three experiments the effects of characteristics of Facebook(i.e. the number of mutual friends, the number of post likes, and the post personalities) on the social rapport and user responses. This study has conducted two-way ANOVA to verity its proposed research hypotheses. Based on three experiments, this study found that both the effects of the number of post likes and the number of post likes on the social rapport were not significant. Based upon empirical findings, this study has demonstrated how the effects of social rapports in SNSs were different from those of previous studies, and brought more attentions to the relevant literature.
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