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Automated Data Collection with R: A Practical Guide to Web Scraping and Text Mining
book

Automated Data Collection with R: A Practical Guide to Web Scraping and Text Mining

by Simon Munzert, Christian Rubba, Peter Meissner, Dominic Nyhuis
January 2015
Intermediate to advanced
480 pages
14h 15m
English
Wiley
Content preview from Automated Data Collection with R: A Practical Guide to Web Scraping and Text Mining

12 Collaboration networks in the US Senate

The inner workings of legislatures are inherently difficult to investigate. Political scientists have been interested in collaborations among parliamentarians as explanatory factors in legislative behavior for decades. Scholars have encountered difficulties, however, in collecting comprehensive data over time to investigate patterns of cooperation. The advent of large-scale, machine-readable databases on legislative behavior have opened up promising new research avenues in this regard. Among these, scholars have considered the possibility of treating bill cosponsorships as proxies for legislative cooperation in the United States. We follow this lead and investigate who cooperates with whom in the US Senate.

Every bill that is introduced to the US Senate is tied to one senator as its main sponsor, but other senators are free to cosponsor a bill in order to support the bill's content—a common practice in senatorial procedures. In fact, in many instances, a bill will have numerous cosponsors. Several authors have recently begun to truly appreciate the network-like structure in bill cosponsorships that is best analyzed using network-analytic methodology.1 Using the rich and well accessible data source on bill cosigners provides researchers with an interesting insight into the black box of collaboration among senators. What is more, bill cosponsorships are moving targets. New proposals are constantly put on record. Being able to collect ...

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Publisher Resources

ISBN: 9781118834800Purchase book