What is polarization?
Polarization occurs when people divide into subgroups that are very different from one another. For example, income polarization occurs when some are very rich while others are very poor, and there is little middle ground. I am particularly interested in political polarization, which has become common throughout the world and especially in the United States, where it occurs along ideological (e.g. conservative/liberal) and partisan (e.g. Republican/Democrat) lines.
Research on polarization
I use signed backbone networks (networks where some links are positive, and others are negative) to distinguish between two kinds of political polarization in the US Senate and House of Representatives. Weak polarization occurs when Republicans and Democrats don't work together because they are just interested in different issues, creating an "Us and Them" situation. In contrast, strong polarization occurs when the Republicans and Democrats actively oppose each other, creating an "Us versus Them" situation. I've found that both forms of polarization have increased since the late 1970s, but that in some cases polarization can actually help legislators pass bills.
Data on legislative networks
My research on polarization relies on generating networks among legislators, which are inferred from their bill sponsorship activities. By combining functions in the incidentally and backbone packages, it is possible to generate custom legislative networks. These networks can be customized by session (108 – present), chamber (Senate or House), policy area (32 topics), and network type (binary or signed). A detailed example is available here.
Papers and data about polarization
for more, please visit this page
Aref, S. and Neal, Z. P. (2020). Detecting coalitions by optimally partitioning signed networks of political collaboration. Scientific Reports, 10, 1506. https://doi.org/ 10.1038/s41598-020-58471-z
Neal, Z. P., Domagalski, R., and Yan, X. (2022). Homophily in collaborations among US House Representatives, 1981–2018. Social Networks, 68, 97-106. https://doi.org/10.1016/j.socnet.2021.04.007
Aref. S. and Neal, Z. P. (2021). Identifying hidden coalitions in the US House of Representatives by optimally partitioning signed networks based on generalized balance. Scientific Reports, 11, 19939. https://doi.org/10.1038/s41598-021-98139-w
Collaborators on polarization
Dr. Samin Aref, Max Planck Institute for Demographic Research
Xiaoqin Yan, Sociology Department, North Carolina State University