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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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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
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 Governments 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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