한국인터넷방송통신학회논문지 (The Journal of the Institute of Internet, Broadcasting and Communication)

  • 제17권2호
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  • Pages.75-82
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  • 2017
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  • 2289-0238(pISSN)
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  • 2289-0246(eISSN)
한국인터넷방송통신학회 (The Institute of Internet, Broadcasting and Communication)
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블루투스 접촉 데이터를 이용한 사회관계구조 검출 알고리즘

Detection Algorithm of Social Community Structure based on Bluetooth Contact Data

  • 웬꽁빈 (울산대학교 전기전자컴퓨터공학과) ;
  • 윤석훈 (울산대학교 전기전자컴퓨터공학과)
  • 투고 : 2017.01.09
  • 심사 : 2017.04.07
  • 발행 : 2017.04.30
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초록

본 논문에서는 사회관계구조에 초점을 맞춘 사회관계망 분석을 고려한다. 사회관계망은 많은 사회집단으로 구성되어 있으며, 사회관계 구조 특성으로 인하여 같은 사회집단 내의 노드들은 서로 강한 유대관계를 가지고 있으며 다른 사회집단에 속한 노드와는 상대적으로 약한 유대를 가지게 된다. 사회관계망에서의 사회관계구조 검출은 사람들의 행동 및 상호작용의 분석과 예측을 가능하게 한다. 본 논문에서는 사회관계구조와 사회집단을 검출하기 위하여 사람들이 소지하는 스마트기기의 실제 블루투스 접촉 데이터를 이용한다. 네트워크 노드 간 유대를 추정하기 위한 다양한 유사도 측정 방식과 클러스터링을 기반으로 하는 사회관계구조 검출 방안을 제시한다. 제안하는 방안을 검증하기 위하여 교유관계 특성을 이용하는 성능측정방안을 이용한다.

In this paper, we consider social network analysis that focuses on community detection. Social networks embed community structure characteristics, i.e., a society can be partitioned into many social groups of individuals, with dense intra-group connections and much sparser inter-group connections. Exploring the community structure allows predicting as well as understanding individual's behaviors and interactions between people. In this paper, based on the interaction information extracted from a real-life Bluetooth contacts, we aim to reveal the social groups in a society of mobile carriers. Focusing on estimating the closeness of relationships between network entities through different similarity measurement methods, we introduce the clustering scheme to determine the underlying social structure. To evaluate our community detection method, we present the evaluation mechanism based on the basic properties of friendship.

키워드

참고문헌

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