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http://dx.doi.org/10.5351/KJAS.2017.30.3.403

Cosponsorship networks in the 17th National Assembly of Republic of Korea  

Park, Chanmoo (Department of Statistics, Seoul National University)
Jang, Woncheol (Department of Statistics, Seoul National University)
Publication Information
The Korean Journal of Applied Statistics / v.30, no.3, 2017 , pp. 403-415 More about this Journal
Abstract
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.
Keywords
centrality; cosponsorship; exponential random graph model; mutuality; party match;
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  • Reference
1 Bastian, M., Heymann, S., and Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks, International AAAI Conference on Weblogs and Social Media, 8, 361-362.
2 Chang, D. (2011). Policy networks in the 17th National Assembly of Korea: an analysis of co-sponsorship and friendship Ties, Bulletin of the Korean Association of Party Studies, 10, 157-178.
3 Fowler, J. H. (2006). Connecting the Congress: A study of cosponsorship networks. Political Analysis, 456-487.
4 Hunter, D. R., Handcock, M. S., Butts, C. T., Goodreau, S. M., and Morris, M. (2008). ergm: A package to fit, simulate and diagnose exponential-family models for networks, Journal of Statistical Software, 24, nipha 54860.
5 Jacomy, M., Venturini, T., Heymann, S. and Bastian, M. (2014). ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software, PLoS ONE, 9, e98679.   DOI
6 Krivitsky, P. N. (2012). Exponential-family random graph models for valued networks, Electronic Journal of Statistics, 6, 1100-1128.   DOI
7 Krivitsky, P. N. (2016). ergm.count: Fit, Simulate and Diagnose Exponential-Family Models for Networks with Count Edges, The Statnet Project http://www.statnet.org, R package version 3.2.2, http://CRAN.R-project.org/package=ergm.count.
8 Lee, B. K. and Youm, Y. S. (2009). Identifying the structure of co-signing networks among the 17th Korean congressmen in the standing committee of health and welfare: By using p-net modeling, Journal of Contemporary Society and Culture, 29, 33-60.