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The Manifesto Corpus: a new resource for research on political parties and quantitative text analysis

[journal article]

Merz, Nicolas
Regel, Sven
Lewandowski, Jirka

Abstract

This article presents a digital, open-access, multilingual, annotated corpus of electoral programs. It complements the recent methodological innovations in (semi-) computerized content analysis by providing a large, standardized text corpus for the political science community. The corpus is based on... view more

This article presents a digital, open-access, multilingual, annotated corpus of electoral programs. It complements the recent methodological innovations in (semi-) computerized content analysis by providing a large, standardized text corpus for the political science community. The corpus is based on the collection of the Manifesto Project, which comprises of (at the time of writing) the largest hand-annotated text corpus of electoral programs available. Since 2009 the project’s costly and time-intensive procedure of collecting and coding documents has been fully digitized. As a result, it now provides more than 1800 machine readable documents from 40 different countries. Six hundred of these documents contain content-analyzed annotations at the level of single (quasi-) sentences, which correspond to the Manifesto Project coding scheme. Additionally, the corpus will continually be extended by incorporating new elections and digitizing older documents. The database also provides meta-information for each document (eg. party, election, language, etc.) that allow it to be referenced back to the Manifesto Dataset. The corpus is stored in a standardized format in an online database, and an API and R package (manifestoR) guarantee easy access.... view less

Keywords
election campaign; political program; party; content analysis; text analysis; quantitative method; data bank

Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods

Free Keywords
R package; electoral programs; text corpus

Document language
English

Publication Year
2016

Page/Pages
p. 1-8

Journal
Research and Politics, 3 (2016) 2

ISSN
2053-1680

Status
Published Version; peer reviewed

Licence
Creative Commons - Attribution-NonCommercial 3.0


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© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.