Abstract
We study community structure in time-dependent legislation cosponsorship networks in the Peruvian Congress, and we compare them briefly to legislation cosponsorship networks in the US Senate. To study these legislatures, we employ a multilayer representation of temporal networks in which legislators in each layer are connected to each other with a weight that is based on how many bills they cosponsor. We then use multilayer modularity maximization to detect communities in these networks. From our computations, we are able to capture power shifts in the Peruvian Congress during 2006-2011. For example, we observe the emergence of 'opportunists', who switch from one community to another, as well as cohesive legislative communities whose initial component legislators never change communities. Interestingly, many of the opportunists belong to the group that won the majority in Congress.
Original language | English |
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Article number | cnw004 |
Pages (from-to) | 127-144 |
Number of pages | 18 |
Journal | Journal of Complex Networks |
Volume | 5 |
Issue number | 1 |
DOIs | |
State | Published - 1 Mar 2017 |
Bibliographical note
Funding Information:We thank James Fowler for helpful discussions and for his help in setting up this collaboration. JMM also acknowledges the Center for Social Complexity at George Mason University and the Department of Social Sciences at Pontificia Universidad Católica del Peru for their support during the initial part of this work. We also thank Peter Mucha for helpful comments. Funding S.H.L. was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (grant no. 2013R1A1A2011947), and M.A.P. was supported by the European Commission FET-Proactive project PLEXMATH (grant no. 317614). S.H.L. and M.A.P. also acknowledge support from the Engineering and Physical Sciences Research Council (EPSRC) through grant no. EP/J001759/1. J.M.M. acknowledges support from the University of Washington eScience Institute and data-science grants from the Alfred P. Sloan Foundation, the Gordon and Betty Moore Foundation, and the Washington Research Foundation.
Publisher Copyright:
© The authors 2016. Published by Oxford University Press. All rights reserved.
Keywords
- Multilayer networks
- Political cosponsorship networks
- Time-dependent community structure