• Title, Summary, Keyword: Network analysis

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An Improved Method of Character Network Analysis for Literary Criticism: A Case Study of

  • Kwon, Ho-Chang;Shim, Kwang-Hyun
    • International Journal of Contents
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    • v.13 no.3
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    • pp.43-48
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    • 2017
  • As a computational approach to literary criticism, the method of character network analysis has attracted attention. The character network is composed of nodes as characters and links as relationship between characters, and has been used to analyze literary works systematically. However, there were limitations in that relationships between characters were so superficial that they could not reflect intimate relationships and quantitative data from the network were not interpreted in depth regarding meaning of literary works. In this study, we propose an improved method of character network analysis through a case study on the play . First, we segmented the character network into a dialogue network focused on speaker-to-listener relationship and an opinion network focused on subject-to-object relationship. We analyzed these networks in various ways and discussed how analysis results could reflect structure and meaning of the work. Through these studies, we strived to find a way of organic and meaningful connection between literary criticism in humanities and network analysis in computer science.

Social Network Analysis to Analyze the Purchase Behavior Of Churning Customers and Loyal Customers (사회 네트워크 분석을 이용한 충성고객과 이탈고객의 구매 특성 비교 연구)

  • Kim, Jae-Kyeong;Choi, Il-Young;Kim, Hyea-Kyeong;Kim, Nam-Hee
    • Korean Management Science Review
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    • v.26 no.1
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    • pp.183-196
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    • 2009
  • Customer retention has been a pressing issue for companies to get and maintain the loyal customers in the competing environment. Lots of researchers make effort to seek the characteristics of the churning customers and the loyal customers using the data mining techniques such as decision tree. However, such existing researches don't consider relationships among customers. Social network analysis has been used to search relationships among social entities such as genetics network, traffic network, organization network and so on. In this study, a customer network is proposed to investigate the differences of network characteristics of churning customers and loyal customers. The customer networks are constructed by analyzing the real purchase data collected from a Korean cosmetic provider. We investigated whether the churning customers and the loyal customers have different degree centralities and densities of the customer networks. In addition, we compared products purchased by the churning customers and those by the loyal customers. Our data analysis results indicate that degree centrality and density of the churning customer network are higher than those of the loyal customer network, and the various products are purchased by churning customers rather than by the loyal customers. We expect that the suggested social network analysis is used to as a complementary analysis methodology with existing statistical analysis and data mining analysis.

Centrality Measures for Bibliometric Network Analysis (계량서지적 네트워크 분석을 위한 중심성 척도에 관한 연구)

  • Lee Jae-Yun
    • Journal of the Korean Society for Library and Information Science
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    • v.40 no.3
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    • pp.191-214
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    • 2006
  • Recently, some bibliometric researchers tried to use the centrality analysis methods and the centrality measures which are standard tools in social network analysis. However the traditional centrality measures originated from social network analysis could not deal with weighted networks such as co-citation networks. In this study. new centrality measures for analyzing bibliometric networks with link weights are suggested and applied to three real network data, including an author co-citation network, a co-word network, and a website co-link network. The results of centrality analyses in these three cases can be regarded as Promising the usefulness of suggested centrality measures, especially in analyzing the Position and influence of each node in a bibliometric network.

Trend Analysis of Data Mining Research Using Topic Network Analysis

  • Kim, Hyon Hee;Rhee, Hey Young
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.5
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    • pp.141-148
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    • 2016
  • In this paper, we propose a topic network analysis approach which integrates topic modeling and social network analysis. We collected 2,039 scientific papers from five top journals in the field of data mining published from 1996 to 2015, and analyzed them with the proposed approach. To identify topic trends, time-series analysis of topic network is performed based on 4 intervals. Our experimental results show centralization of the topic network has the highest score from 1996 to 2000, and decreases for next 5 years and increases again. For last 5 years, centralization of the degree centrality increases, while centralization of the betweenness centrality and closeness centrality decreases again. Also, clustering is identified as the most interrelated topic among other topics. Topics with the highest degree centrality evolves clustering, web applications, clustering and dimensionality reduction according to time. Our approach extracts the interrelationships of topics, which cannot be detected with conventional topic modeling approaches, and provides topical trends of data mining research fields.

Analyzing Organizational Networks Based on a Combination of Network Analysis with ABM Simulation

  • Kim, Dae-Joong
    • New Physics: Sae Mulli
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    • v.67 no.5
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    • pp.602-607
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    • 2017
  • This paper reports the results of the first case study to combine network analysis with Agent-based modeling (ABM) simulation to build a theoretical and practical framework to explain how individual rational behaviors affect organizational cooperation or trust. Through the combination, I tried to overcome the general limitations of network analysis due to past facts. Network analysis has shown changes from past to the present. Thus, discovering or testing a generalized pattern and predicting the next changes are difficult, as is collecting network data. One of the ways of overcoming the weakness of network analysis is to simulate network models by using ABM. For this study, I used a real case with two time periods (2003 and 2006). The results show that the cross-fertilization of the two approaches can be a useful theoretical and practical framework in explaining and predicting emergent behaviors between micro-macro structures in organizations. In addition, this study can give practical insight, based on the information of networks and ABM simulation, to leaders about how they can effectively manage (allocate or reallocate) their human resources and resolve conflicts between organizational members to make them cooperated with one another.

Integrated Ground-Underground Spatial Network for Urban Spatial Analysis (도시 공간분석을 위한 지상·지하 공간 네트워크)

  • Piao, Gensong;Choi, Jaepil
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.34 no.4
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    • pp.69-76
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    • 2018
  • The purpose of this study is to propose and verify a spatial network construction method that integrated roads and subway lines to improve the predictability of the urban spatial analysis model. The existing axial map for urban spatial analysis did not reflect the subway line that serves as an important moving space in modern cities. To improve this axial map, proposed a Ground-Underground Spatial Network by integrating the underground spatial network with the axial map. As a result of the integration analysis, the Ground-Underground Spatial Network(GUSN) were similar to the movement frequency. Correlation of GUSN was 0.723, which showed higher explanatory power than correlation coefficient of 0.575 in axial map. The result of this study is expected to be a theoretical basis for constructing spatial network in urban space analysis with subway.

Comparison of Recommendation Using Social Network Analysis with Collaborative Filtering in Social Network Sites (SNS에서 사회연결망 기반 추천과 협업필터링 기반 추천의 비교)

  • Park, Sangun
    • Journal of Information Technology Services
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    • v.13 no.2
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    • pp.173-184
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    • 2014
  • As social network services has become one of the most successful web-based business, recommendation in social network sites that assist people to choose various products and services is also widely adopted. Collaborative Filtering is one of the most widely adopted recommendation approaches, but recommendation technique that use explicit or implicit social network information from social networks has become proposed in recent research works. In this paper, we reviewed and compared research works about recommendation using social network analysis and collaborative filtering in social network sites. As the results of the analysis, we suggested the trends and implications for future research of recommendation in SNSs. It is expected that graph-based analysis on the semantic social network and systematic comparative analysis on the performances of social filtering and collaborative filtering are required.

A Study on the Sensitivity Analysis of GERT Network (GERT Network의 감도분석(感度分析)에 관한 고찰(考察))

  • Lee, Sang-Do;Jeong, Jung-Hui;Park, Gi-Ju
    • Journal of Korean Institute of Industrial Engineers
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    • v.9 no.2
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    • pp.47-53
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    • 1983
  • In this paper, a sensitivity analysis is proceeded to improve the network of manufacturing process by converting the qualitative network into GERT Network and by finding equivalent probability, MFG's of variables and sensitivity equation in GERT Network. Sensitivity analysis of GERT Network is important in evaluating, reviewing and improving system. System improvement in GERT Network is achieved by increasing the equivalent probability and by decreasing the equivalent time.

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Social Network Analysis Using Booth Visiting Data (부스 방문데이터를 활용한 사회 네트워크 분석)

  • Park, Deuk Hee;Choi, Il Young;Kim, Hyea Kyeong;Kim, Jae Kyeong
    • Journal of Information Technology Services
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    • v.10 no.1
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    • pp.35-46
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    • 2011
  • As development of exhibition, it has been an important issue to analyze exhibition for the next success of exhibition. A lot of existing researches have focused on the exhibitor's and visitor's satisfaction problem. However, the exhibitor's satisfaction and success of exhibition come from the analysis of exhibition in the network level. Booths composing exhibition are regarded as nodes in network, so the trace of visitors visiting booths can construct the arc of networks. The purpose of this study is to analyze the booth visiting pattern and components of network through social network analysis using data collected in the $17^{th}$ International KIDS & EDU EXPO for Children. This research is the first approach of network-leveled analysis of exhibition, and the result of network analysis is helpful to support the booth arrangement in next exhibition. Our analysis results the following implications. First, Booths with high degree centrality or betweenness centrality should be deployed in the wide space or corner of the exhibition hall. Finally, booths within a block should be deployed in the same space of the exhibition hall to provide convenience to the visitors and to enhance exhibition performance.

A Study on the Research Trends to Flipped Learning through Keyword Network Analysis (플립러닝 연구 동향에 대한 키워드 네트워크 분석 연구)

  • HEO, Gyun
    • Journal of Fisheries and Marine Sciences Education
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    • v.28 no.3
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    • pp.872-880
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    • 2016
  • The purpose of this study is to find the research trends relating to flipped learning through keyword network analysis. For investigating this topic, final 100 papers (removed due to overlap in all 205 papers) were selected as subjects from the result of research databases such as RISS, DBPIA, and KISS. After keyword extraction, coding, and data cleaning, we made a 2-mode network with final 202 keywords. In order to find out the research trends, frequency analysis, social network structural property analysis based on co-keyword network modeling, and social network centrality analysis were used. Followings were the results of the research: (a) Achievement, writing, blended learning, teaching and learning model, learner centered education, cooperative leaning, and learning motivation, and self-regulated learning were found to be the most common keywords except flipped learning. (b) Density was .088, and geodesic distance was 3.150 based on keyword network type 2. (c) Teaching and learning model, blended learning, and satisfaction were centrally located and closed related to other keywords. Satisfaction, teaching and learning model blended learning, motivation, writing, communication, and achievement were playing an intermediary role among other keywords.