Measuring Polarization in High-Dimensional Data: Method and Application to Congressional Speech
Year: 2016
Type: article
Abstract: Standard measures of segregation or polarization are inappropriate for high-dimensional data such as Internet browsing histories, item-level purchase data, or text. We develop a model-based measure of polarization that can be applied to such data. We illustrate the measure with an application to the partisanship of speech in the US Congress from 1872 to the present. We find that speech has become more polarized across party lines over time, with a clear trend break around 1980. *E-mail:
Authors: Matthew Gentzkow, Jesse M. Shapiro, Matt Taddy
Language: English
Subfield: General Social Sciences
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2506486438