Ulrich Matter

Omar A. Guerrero, Ulrich Matter

Cooperation in the form of vote trading, also known as logrolling, is central for law-making processes, shaping the development of democratic societies. Empirical evidence of logrolling is scarce and limited to highly specific situations because existing methods are not easily applicable to broader contexts. We have developed a general and scalable methodology for revealing a network of vote traders, allowing us to measure logrolling on a large scale. Analysis on more than 9 million votes spanning 40 years in the U.S. Congress reveals a higher logrolling prevalence in the Senate and an overall decreasing trend over recent congresses, coincidental with high levels of political polarization. Our method is applicable in multiple contexts, shedding light on many aspects of logrolling and opening new doors in the study of hidden cooperation.

Ulrich Matter

The rise of the programmable web offers new opportunities for the empirically driven social sciences. The access, compilation and preparation of data from the programmable web for statistical analysis can, however, involve substantial up-front costs for the practical researcher. The R-package RWebData provides a high-level framework that allows data to be easily collected from the programmable web in a format that can directly be used for statistical analysis in R (R Core Team 2013) without bothering about the data's initial format and nesting structure. It was developed specifically for users who have no experience with web technologies and merely use R as a statistical software. The core idea and methodological contribution of the package are the disentangling of parsing web data and mapping them with a generic algorithm (independent of the initial data structure) to a flat table-like representation. This paper provides an overview of the high-level functions for R-users, explains the basic architecture of the package, and illustrates the implemented data mapping algorithm.