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Archived Attributes: An Internet-Text Approach to Measuring Legislator Attitudes and Behavior

Published online by Cambridge University Press:  09 December 2020

Emily Kalah Gade Open the ORCID record for Emily Kalah Gade [Opens in a new window] ,
Sarah Dreier ,
John Wilkerson  and
Anne Washington Open the ORCID record for Anne Washington [Opens in a new window]
Emily Kalah Gade*
Affiliation:
Emory University, Atlanta, Georgia, USA
Sarah Dreier
Affiliation:
University of Washington, Seattle, Washington, USA
John Wilkerson
Affiliation:
University of Washington, Seattle, Washington, USA
Anne Washington
Affiliation:
NYU Steinhardt, New York, USA
*
*Corresponding author. E-mail: [email protected]
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Abstract

The Internet Archive curated a 90-terabyte sub-collection of captures from the US government's public website domain (‘.gov’). Such archives provide largely untapped resources for measuring attributes, behaviors and outcomes relevant to political science research. This study leverages this archive to measure a novel dimension of federal legislators' religiosity: their proportional use of religious rhetoric on official congressional websites (2006–2012). This scalable, time-variant measure improves upon more costly, time-invariant conventional approaches to measuring legislator attributes. The authors demonstrate the validity of this method for measuring legislators' public-facing religiosity and discuss the contributions and limitations of using archived Internet data for scientific analysis. This research makes three applied methodological contributions: (1) it develops a new measure for legislator religiosity, (2) it models an improved, more comprehensive approach to analyzing congressional communications and (3) it demonstrates the unprecedented potential that archived Internet data offer to researchers seeking to develop meaningful, cost-effective approaches to analyzing political phenomena.

Keywords

religiosityUS Congressweb archivesmethodology‘big data’text-as-data
Type
Letter
Information
British Journal of Political Science , Volume 51 , Issue 4 , October 2021 , pp. 1734 - 1741
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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Gade et al. Dataset

Dataset

https://doi.org/10.7910/DVN/GNL6XG
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