• Title/Summary/Keyword: ERGM for Valued Networks

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An Empirical Comparison of Statistical Models for Pre-service Teachers' Help Networks using Binary and Valued Exponential Random Graph Models (예비교원의 도움 네트워크에 관한 통계 모형의 경험적 비교: 이항 및 가중 ERGM을 중심으로)

  • Kim, Sung-Yeun;Kim, Chong Min
    • The Journal of the Korea Contents Association
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    • v.20 no.4
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    • pp.658-672
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    • 2020
  • The purpose of this study is to empirically compare statistical models for pre-service teachers' help networks. We identified similarities and differences based on the results of the binary and valued ERGM. Research questions are as follows: First, what are the similarities of factors influencing the binary/valued help network for pre-service teachers? Second, what are differences of factors influencing the binary/valued help network for pre-service teachers? We measured 42 pre-service teachers with focus on their help and friend networks, happiness, and personal characteristics. Results indicated that, first, the similar factors influencing the binary and valued help network of pre-service teachers were local dependencies (reciprocity, transitivity), similarity (major, gender), activity (early childhood education, negative emotion), popularity (early childhood education) and multiplicity (friend network). Second, the difference between factors affecting pre-service teacher's binary and valued help network was the effect of activity (physical education) and popularity (GPA, negative emotion). Based on these findings, we presented implications.

Cosponsorship networks in the 17th National Assembly of Republic of Korea (17대 국회의 공동법안발의에 관한 네트워크 분석)

  • Park, Chanmoo;Jang, Woncheol
    • The Korean Journal of Applied Statistics
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    • v.30 no.3
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    • pp.403-415
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    • 2017
  • In this paper, we investigate cosponsorship networks found in the 17th National Assembly of Republic of Korea. New legislation should be sponsored by at least 10 legislators including one main sponsor. Cosponsorship networks can be constructed, using directional links from cosponsors of legislation to its main sponsor; subsequently, these networks indicate the social relationships among the legislators. We apply Exponential Random Graph Model (ERGM) for valued networks to capture structural properties and the covariate effects of networks. We find the effect of the same party has the greatest influence on the composition of the network. Mutuality also plays an important role in the cosponsorship network; in addition, the effect of the number of elections won by a legislator has a small but significant influence.