• KIPS Transactions on Software and Data Engineering
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• v.4 no.1
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• pp.37-44
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• 2015

In traditional social network analysis, the betweenness centrality measure has been heavily used to identify the relative importance of nodes. Since the time complexity to calculate the betweenness centrality is very high, however, it is difficult to get it of each node in large-scale social network where there are so many nodes and edges. In our past study, we defined a new type of network, called the expanded ego network, which is built only with each node's local information, i.e., neighbor information of the node's neighbor nodes, and also defined a new measure, called the expanded ego betweenness centrality. In this paper, We propose algorithm that quickly computes expanded ego betweenness centrality by exploiting structural properties of expanded ego network. Through the experiment with virtual network used Barab$\acute{a}$si-Albert network model to represent the generic social network and facebook network to represent actual social network, We show that the node's importance rank based on the expanded ego betweenness centrality has high similarity with that the node's importance rank based on the existing betweenness centrality. We also show that the proposed algorithm computes the expanded ego betweenness centrality quickly than existing algorithm.

• Journal of the Korean Society for information Management
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• v.32 no.1
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• pp.153-169
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• 2015

The combined approach of using ego-centric network analysis and dynamic citation network analysis for refining the result of LDA-based topic modeling was suggested and examined in this study. Tow datasets were constructed by collecting Web of Science bibliographic records of White LED and topic modeling was performed by setting a different number of topics on each dataset. The multi-assigned top keywords of each topic were re-assigned to one specific topic by applying an ego-centric network analysis algorithm. It was found that the topical cohesion of the result of topic modeling with the number of topic corresponding to the lowest value of perplexity to the dataset extracted by SPLC network analysis was the strongest with the best values of internal clustering evaluation indices. Furthermore, it demonstrates the possibility of developing the suggested approach as a method of multi-faceted research trend detection.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.5
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• pp.209-216
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• 2013

In traditional social network analysis, the betweenness centrality measure has been heavily used to identify the relative importance of nodes in terms of message delivery. Since the time complexity to calculate the betweenness centrality is very high, however, it is difficult to get it of each node in large-scale social network where there are so many nodes and edges. In this paper, we define a new type of network, called the expanded ego network, which is built only with each node's local information, i.e., neighbor information of the node's neighbor nodes, and also define a new measure, called the expended ego betweenness centrality. Through the intensive experiment with Barab$\acute{a}$si-Albert network model to generate the scale-free networks which most social networks have as their embedded feature, we also show that the nodes' importance rank based on the expanded ego betweenness centrality has high similarity with that based on the traditional betweenness centrality.

• Proceedings of the KAIS Fall Conference
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• 2010.11b
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• pp.721-724
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• 2010

경제 불황으로 기업들의 구조조정이 가시화되면서 고용 축소와 청년실업이 늘어나면서 창업이나 경영을 통해 경제적 독립과 자아실현을 이루려는 창업가들이 점차 증가하고 있으며, 그에 따른 학계 연구의 필요성도 대두되고 있다. 본 연구는 이러한 연구 필요성에 따라 창업의도에 결정요인으로서 사회적 네트워크와 자아 효능감을 개인특성요인의 핵심변수로 설정하여 창업활동과 창업목표달성에 미치는 영향을 중심으로 살펴보았다. 본 연구를 위해 국내 창업가를 대상으로 208부를 분석에 이용하였다. 가설검증 결과, 사회적 네트워크의 강한 유대가 창업의도에 유의한 영향을 미치는 것으로 나타났으며, 창업활동에는 약한 유대가 영향을 나타나는 것으로 분석되었으며, Podolny와 Baron(1997) 네트워크의 특성에 따라 네트워크 강도의 효과가 달라질 수 있다는 주장과 일치하는 것을 발견 할 수 있었다. 또한 자아효능감은 창업활동보다 창업의도에 더 영향을 미치는 것으로 나타났다. 이러한 연구결과를 통해 목표달성을 분석한 결과 창업의도보다 창업활동이 목표달성에 더 유의 한 영향을 미치는 것을 알 수 있었다.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1237-1248
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• 2011

Social network analysis(SNA) has been recently applied to business areas such as social network services (such as Facebook and Twitter). In addition, the mobile telecommunication field attempts to analyze CDR(call detail record) data and apply customer relationship management and customer churn management through the use of social network analysis. The paper analyzes links between ego and alter based on ego-network and discovers four kinds of customer roles and then provides insights as a tool for customer relationship management or customer management.

• 한국HCI학회:학술대회논문집
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• 2006.02b
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• pp.389-395
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• 2006

이 연구는 사회관계망의 형태와 구성원에 관한 정보를 분석하여 모바일로 서비스하는 것에 관한 연구이다. 사람들은 얽히고 설킨 다양한 인간 관계를 갖고 있다. 인간 관계를 유지하기 위해 여러 채널을 통해 커뮤니케이션을 하게 된다. 실생활에서 갖게 되는 인간 관계의 형태와 가장 비슷한 형태의 커뮤니케이션 채널은 휴대전화이다. 사회관계망 이론의 관점에서 보면 휴대전화의 사용은 기존의 인맥에서 친밀도가 적은 사람에게는 영향이 크지 않지만 친밀도가 높은 사람에게는 더욱 친밀하게 만드는 영향을 준다. 이 연구에서는 휴대전화의 통화상대, 통화시간, 통화량 등의 정보가 나타나있는 통화기록에 기반하여 일정기간 동안 통화한 상대들을 추출하였다. 통화기록의 정보를 사회 관계망 분석 도구인 UCINET으로 분석한 결과 휴대전화를 매개로 한 사회관계망의 형태가 자아 중심적 관계망과 같은 형태를 지니고 있다는 사실을 도출해냈다. 그리고 자아 중심적 관계망의 분석 기법을 이용하여 관계망의 중심에 있는 자아와 통화상대와의 관계를 분석하였다. 또한 통화상대들의 휴대전화 통화기록을 통해 서로 관계가 있는지에 대해 알아보았다. 그 결과 자아의 인맥 네트워크 안에 있는 사람들을 그룹화하고 그들의 나이, 성별, 직업에 의해 어떠한 특징을 갖는 그룹인지 분석하였다. 이러한 연구는 휴대전화를 통해 자신의 인간 관계 형태를 파악하여 관계를 관리하고 유지할 수 있는 새로운 모바일 서비스 개발을 위해 활용될 수 있을 것이다.

• Journal of the Korean Society for information Management
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• v.31 no.4
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• pp.161-178
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• 2014

Recently, many information services allow users to collaborate to produce and use information. Sharing information is also important for users who have similar taste or interest. As various channels are available for users to share their experiences and knowledge, users' data have also been accumulated within the information services. This study collected movie lists made by users of IMDB service. Co-word analysis and ego-centered network analysis were adapted to discover relevant information for users who chose a specific movie. Three factors of movies including movie title, director and genre were used to present related movie information. Movie title is an effective feature to present related movies with various aspects such as theme or characters and the popularity of directors affects on identifying related directors. Genre is not useful to find related movies due to the complexity in the topic of a movie.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.284-291
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• 2022

People use various tools to present themselves including Social Network Services(SNS hereafter). This study categorized three types of presentation of self, which are genuine, ideal, and social self, and based on Goffman's Impression Management Framework, investigated if these types of presentations have any patterns related to SNS posting styles. Especially, we focused on the styles of hashtags including if hashtags are used in the main tests, if hashtags are hidden, and what kinds of words are used for hashtags. Using 450 posting data uploaded to the Instagram, we found that the posting presenting ideal self show very high rate of using hidden hashtags(98%) and using common expressions(97%), which are not the case for genuine and social self types. This results imply that people concern more about their impressions especially when they present their ideal self on SNS, partially confirming Goffman's Impression Management Framework.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.7-32
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• 2017

Recently, deep learning has been rapidly spreading as an innovative machine learning technique in various domains. This study explored the research trends of deep learning via modified ego centered topic citation analysis. To do that, a few seed documents were selected from among the retrieved documents with the keyword 'deep learning' from Web of Science, and the related documents were obtained through citation relations. Those papers citing seed documents were set as ego documents reflecting current research in the field of deep learning. Preliminary studies cited frequently in the ego documents were set as the citation identity documents that represents the specific themes in the field of deep learning. For ego documents which are the result of current research activities, some quantitative analysis methods including co-authorship network analysis were performed to identify major countries and research institutes. For the citation identity documents, co-citation analysis was conducted, and key literatures and key research themes were identified by investigating the citation image keywords, which are major keywords those citing the citation identity document clusters. Finally, we proposed and measured the citation growth index which reflects the growth trend of the citation influence on a specific topic, and showed the changes in the leading research themes in the field of deep learning.

• The Korean Journal of Applied Statistics
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• v.26 no.1
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• pp.23-36
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• 2013

In this study, we investigate how churn customers (who play a central connector or broker role) affect other customers' churn in their call networks with ego-network analysis using call data of a mobile telecom company in Korea. As a result of investigating Reciprocal Network, we found a relationship of attrition among churn customers. Churn provokers who influence other customers' attrition exist in customer churn networks. The characteristics of churn provokers is that they play a central connector and broker role in their groups. The proportion of churn provokers increases and the churn provoker's influence increases because the network is a reciprocal one.