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Topic Based Hierarchical Network Analysis for Entrepreneur Using Text Mining

텍스트 마이닝을 이용한 주제기반의 기업인 네트워크 계층 분석

  • Lee, Donghun (Dept. of Industrial and Management Engineering, Incheon National University) ;
  • Kim, Yonghwa (Dept. of Industrial and Management Engineering, Incheon National University) ;
  • Kim, Kwanho (Dept. of Industrial and Management Engineering, Incheon National University)
  • Received : 2018.05.24
  • Accepted : 2018.07.14
  • Published : 2018.08.31

Abstract

The importance of convergence activities among business is increasing due to the necessity of designing and developing new products to satisfy various customers' needs. In particular, decision makers such as CEOs are required to participate in networks between entrepreneurs for being connected with valuable convergence partners. Moreover, it is important for entrepreneurs not only to make a large number of network connections, but also to understand the networking relationship with entrepreneurs with similar topic information. However, there is a difficult limit in collecting the topic information that can show the lack of current status of business and the technology and characteristics of entrepreneur in industry sector. In this paper, we solve these problems through the topic extraction method and analyze the business network in three aspects. Specifically, there are C, S, T-Layer models, and each model analyzes amount of entrepreneurs relationship, network centrality, and topic similarity. As a result of experiments using real data, entrepreneur need to activate network by connecting high centrality entrepreneur when the corporate relationship is low. In addition, we confirmed through experiments that there is a need to activate the topic-based network when topic similarity is low between entrepreneurs.

다양한 고객의 요구를 만족시키기 위한 신제품 설계 및 개발의 필요성 때문에 중소기업 간의 융합 활동의 중요성은 증대하고 있다. 특히, 최고 의사결정을 가지는 중소기업 대표는 적합한 융합 활동 파트너를 구하기 위해 인맥관리는 필수적이다. 한편 기업인들은 많은 양의 인맥을 형성하는 것이 중요할 뿐만 아니라 유사한 토픽정보를 가진 기업인과의 인맥관계를 이해하는 것이 중요하다. 그러나 중소기업의 현황 부재와 산업분야별 기업인들의 기술과 특성을 나타낼 수 있는 토픽정보를 수집하는데 어려운 한계가 존재한다. 본 논문에서는 토픽 추출기법을 통해 이와 같은 문제점을 해결하고 3가지 측면에서 기업 네트워크를 분석한다. 구체적으로 C, S, T-Layer 모델이 있으며 각각의 모델은 인맥의 양, 인맥 중심성, 토픽 유사성을 분석한다. 실 데이터를 통한 실험 결과, 인맥의 양이 적은 경우 중심성이 높은 기업과 네트워크를 강화하여 인맥 네트워크를 활성화 시켜야 할 필요가 있고, 토픽 유사성이 낮은 경우 주제 기반의 네트워크를 활성화 시켜야 할 필요가 있다는 것을 실험을 통해 확인하였다.

Keywords

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The Proposed Framework for Entrepreneur Hierarchical Network Analysis

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The Network Structure Obtained Using C-Layer Model

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The Network Structure Obtained using S-layer Model (The value in a node for eachuser represents that user’scentrality)

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The Results of Cumulative Distribution According to Proposed Models

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Network Analysis Results According to Proposed Models

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Examples of Performance Differences the Results According to Proposed Models (Bold and underline means the highest value across models)

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The Results of Proposed Model Score Change and Distribution According to Proposed Models

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The Visualization Results of Top15 Industrial Fields based on S, T-Layer Models

The Overview of Previous Research on Convergence Activities

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Datasets for Learning Color and Word Embedding Models

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Top10 Industrial Fields based on the Numbers of Data Collected

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The Results of Proposed Model Score and Upper Ratios based on C-Layer

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