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Lexical Cohesion Analysis of Political Speech

Published online by Cambridge University Press:  04 January 2017

Beata Beigman Klebanov ,
Daniel Diermeier  and
Eyal Beigman
Beata Beigman Klebanov*
Affiliation:
Kellogg School of Management, MEDS Department, Leverone Hall 554, 2001 Sheridan Road, Evanston, IL60208-2009
Daniel Diermeier*
Affiliation:
Kellogg School of Management, MEDS Department, Leverone Hall 554, 2001 Sheridan Road, Evanston, IL60208-2009
Eyal Beigman*
Affiliation:
Kellogg School of Management, MEDS Department, Leverone Hall 554, 2001 Sheridan Road, Evanston, IL60208-2009
*
e-mail: beata@kellogg.northwestern.edu
e-mail: d-diermeier@kellogg.northwestern.edu (corresponding author)
e-mail: e-beigman@kellogg.northwestern.edu
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Abstract

This article presents a novel automatic method of text analysis aimed at discovering patterns of lexical cohesion in political speech. The unit of analysis are groups of words with related meanings; the software is based on the results of a multiperson annotation experiment that captures reliably identified connections between words in a text. We illustrate the advantages of such a representation by juxtaposing results of a detailed hand-made analysis of Margaret Thatcher's rhetoric with analysis based on the automatically detected groups of words. We both corroborate previous findings regarding Thatcher's rhetorical tools and illuminate additional elements thereof. We suggest that lexical cohesion analysis is a promising technique to bridge the gap between quantitative and qualitative analyses of text as political material, by establishing units that are both robust enough to enable comprehensive coverage and coherent enough to support direct interpretation.

Type
Special Issue: The Statistical Analysis of Political Text
Information
Political Analysis , Volume 16 , Issue 4: Special Issue: The Statistical Analysis of Political Text , Autumn 2008 , pp. 447 - 463
Copyright
Copyright © The Author 2008. Published by Oxford University Press on behalf of the Society for Political Methodology 

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Footnotes

Author's note: Beata Beigman Klebanov is a post-doctoral fellow at the Ford Center for Global Citizenship at the Kellogg School of Management, and at Northwestern Institute for Complex Systems, Northwestern University, Evanston, IL. Her research focuses on semantic analysis of texts from theoretical, experimental, computational, and applied perspectives. Daniel Diermeier is the IBM Distinguished Professor of Regulation and Competitive Practice at the Department of Managerial Economics and Decision Sciences (MEDS), Director of the Ford Motor Company Center for Global Citizenship, all at the Kellogg School of Management; and Professor of Political Science and a Research Fellow at the Northwestern Institute on Complex Systems (NICO), all at Northwestern University. Professor Diermeier specializes in formal models of politics with an emphasis on legislative institutions. Recently he has done extensive work in the use of computational linguistics to study ideology and belief formation in political speech. In 2007 he received the Aspen Institute's Faculty Pioneer Award. Eyal Beigman is a post-doctoral fellow at the Center for Mathematical Studies in Economics and Management Science at the Kellogg School of Management, and at McCormick School of Engineering, Northwestern University, Evanston, IL. His research interests include structural and strategic analysis of voting systems, political speech, and economics of identity. He is also working on a project studying mechanisms and policies in the wireless telecommunication industry.

Conflict of interest statement: None declared.

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