Replication materials are available at †; see http://hdl.handle.net/1902.1/12898. Our special thanks to our indefatigable undergraduate coders Sam Caporal, Katie Colton, Nicholas Hayes, Grace Kim, Matthew Knowles, Katherine McCabe, Andrew Prokop, and Keneshia Washington. Each coded numerous blogs, dealt with the unending changes we made to our coding schemes, and made many important suggestions that greatly improved our work. Matthew Knowles also helped us track down and understand the many scholarly literatures that intersected with our work, and Steven Melendez provided invaluable computer science wizardry; both are coauthors of the open source and free computer program that implements the methods described herein (ReadMe: Software for Automated Content Analysis; see http://gking.harvard.edu/readme). We thank Ying Lu for her wisdom and advice, Stuart Shieber for introducing us to the relevant computer science literature, and http://Blogpulse.com for getting us started with more than a million blog URLs. Thanks to Ken Benoit, Doug Bond, Justin Grimmer, Matt Hindman, Dan Ho, Pranam Kolari, Mark Kantrowitz, Lillian Lee, Will Lowe, Andrew Martin, Burt Monroe, Stephen Purpura, Phil Schrodt, Stuart Shulman, and Kevin Quinn for helpful suggestions or data. Thanks also to the Library of Congress (PA#NDP03-1), the Center for the Study of American Politics at Yale University, the Multidisciplinary Program on Inequality and Social Policy, and the Institute for Quantitative Social Science for research support.
A Method of Automated Nonparametric Content Analysis for Social Science
Article first published online: 28 DEC 2009
DOI: 10.1111/j.1540-5907.2009.00428.x
©2010, Midwest Political Science Association
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How to Cite
Hopkins, D. J. and King, G. (2010), A Method of Automated Nonparametric Content Analysis for Social Science. American Journal of Political Science, 54: 229–247. doi: 10.1111/j.1540-5907.2009.00428.x
Publication History
- Issue published online: 28 DEC 2009
- Article first published online: 28 DEC 2009
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