Isarithmic Maps of Public Opinion Data

As a follow-up to my isarithmic maps of county electoral data, I have attempted to experiment with extending the technique in two ways. First, where the electoral maps are based on data aggregated to the county level, I have sought to generalize the method to accept individual responses for which only zip code data is … Continue reading

High Dimension Visualization in Political Science

Last Friday, I gave a talk illustrating some examples of high-dimension visualization in Political Science. I structured the talk around three arbitrary categories of information visualization: infographics (factoid-packed, inefficient), statistical graphics (argument-making, minimal), and data displays (multidimensional, deep). The slides below are long on examples and short on text, but should be mostly self-explanatory. Header … Continue reading

Dimensionality in Congress

Update: A revised version of this paper, given as a poster at the 2011 Summer Meeting of the Society for Political Methodology, is available here (PDF).   In collaboration with Jacob Montgomery and John Aldrich, I am interested in understanding the relationship between observed (measured) and unobserved (true) dimensionality in Congress. In an ongoing project, … Continue reading

Regionalization via network-constrained clustering

I was interested in applications for a clustering algorithm that works along a network, identifying contiguous partitions, and thought that a good place to start would be identifying regional patterns in electoral preferences. This project represents the early products of this inquiry. I chose county-level data, as counties are small enough to make “interesting” regions, … Continue reading

Partisan structure in online social networks

As part of a continuing project which makes use of data from the social microblogging service Twitter, I presented a paper at the 2010 MPSA in which I derived inferences about elite partisanship and ideology from only the patterns of connections between Twitter users. That is, given only knowledge of which of Twitter’s millions of users were … Continue reading

Party control and political agendas

At the 2010 annual meeting of the Midwest Political Science Association, I presented a paper in which I used a time-series clustering algorithm to identify eras in Congress based on the substantive nature of the Congressional agenda. I found that it was possible to correctly identify changes in party control in the Senate and House, … Continue reading