Portrait of Political Party Polarization1

  title={Portrait of Political Party Polarization1},
  author={James Moody and Peter J. Mucha},
  journal={Network Science},
  pages={119 - 121}
To find out, we measure co-voting similarity networks in the US Senate and trace individual careers over time. Standard network visualization tools fail on dense highly clustered networks, so we used two aggregation strategies to clarify positional mobility over time. First, clusters of Senators who often vote the same way capture coalitions, and allow us to measure polarization quantitatively through modularity (Newman, 2006; Waugh et al., 2009; Poole, 2012). Second, we use role-based… 
Voting Behavior, Coalitions and Government Strength through a Complex Network Analysis
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Separating Controversy from Noise: Comparison and Normalization of Structural Polarization Measures
This work proposes normalization to the existing scores and a minimal set of tests that a score should pass in order for it to be suitable for separating polarized networks from random noise and finds that the choice of method is not as important as normalization.
Disunited Nations? A Multiplex Network Approach to Detecting Preference Affinity Blocs using Texts and Votes
This paper introduces a new approach to estimate preference polarization in multidimensional settings, such as international relations, based on developments in the natural language processing and network science literatures -- namely word embeddings and community detection in multilayer networks.
Analyses of Elite Networks
SNA research on nomination networks and on sampling in networks, particularly on more principled snowball-sampling methods, could help expose biases in the way researchers determine whom to include in their study.
A complex network approach to political analysis: Application to the Brazilian Chamber of Deputies
A network-based methodology to study how political entities evolve over time from the Brazilian Chamber of Deputies, where deputies are nodes and edges are represented by voting similarity among deputies revealed that plurality of ideas is not present at all.
Legislative effectiveness hangs in the balance: Studying balance and polarization through partitioning signed networks
It is shown that changes in bill passage rates are better explained by the partisanship of a chamber's largest coalition, which is identified by partitioning a signed network of legislators into two mutually opposing, but internally cohesive groups.
Legislators’ roll-call voting behavior increasingly corresponds to intervals in the political spectrum
An alternative, discrete, representation that replaces positions (points and distances) with niches (boxes and overlap) is proposed that is sufficient to represent the similarity of roll-call votes by U.S. senators in recent years.
CivisAnalysis : exploring representatives'voting behaviour
CivisAnalysis, an open-source web-based system for the visualization of roll calls in the Brazil’s Chamber of Deputies, provides a unique view of the political history of the country using roll calls of six legislatures as well as six presidential elections.
Analyzing the Bills-Voting Dynamics and Predicting Corruption-Convictions Among Brazilian Congressmen Through Temporal Networks
It is a surprise to us that the high accuracy (up to 90% by the link prediction method) on predicting convictions is achieved only through bills-voting data, without taking into account any financial information beforehand.


Party Polarization in Congress: A Network Science Approach
We measure polarization in the United States Congress using the network science concept of modularity. Modularity provides a conceptually-clear measure of polarization that reveals both the number of
Social Structure from Multiple Networks. I. Blockmodels of Roles and Positions
Networks of several distinct types of social tie are aggregated by a dual model that partitions a population while simultaneously identifying patterns of relations. Concepts and algorithms are
Finding community structure in networks using the eigenvectors of matrices.
  • M. Newman
  • Computer Science
    Physical review. E, Statistical, nonlinear, and soft matter physics
  • 2006
A modularity matrix plays a role in community detection similar to that played by the graph Laplacian in graph partitioning calculations, and a spectral measure of bipartite structure in networks and a centrality measure that identifies vertices that occupy central positions within the communities to which they belong are proposed.
Fast unfolding of communities in large networks
This work proposes a heuristic method that is shown to outperform all other known community detection methods in terms of computation time and the quality of the communities detected is very good, as measured by the so-called modularity.
Voteview.” Retrieved from http://voteview.com
  • 2012
“ Voteview
  • 2012
Social structure from multiple networks: I