From theoretical texts to concept maps: an annotation approach for a distant reading of argumentative text structures

Abstract Assuming that all theoretical texts are at least intentionally aimed at introducing, defining, or relating concepts to one another, we propose a system for categorizing the components of such texts: we argue that on an abstract level, all parts of a theoretical text can be assigned to the categories theses, arguments, and notions. In the article, we explain how these categories were derived and how sthey can be used to create concept maps of theoretical texts, facilitating the analysis of the relation of such concepts in and across texts. We also report on an annotation workflow in which our theoretical concept is subjected to empirical testing and which serves as the basis for (semi-)automatic recognition of the three text parts and the creation of concept maps.

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Publication Details

Journal
Digital Scholarship in the Humanities
Published
2025-08-13
DOI
https://doi.org/10.1093/llc/fqaf089
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

From theoretical texts to concept maps: an annotation approach for a distant reading of argumentative text structures

Gabriel Viehhauser, Radu Tulai, Jan Angermeier, Gökce Taban
Digital Scholarship in the Humanities
Natural Language Processing Techniques
article

From theoretical texts to concept maps: an annotation approach for a distant reading of argumentative text structures

Gabriel Viehhauser, Radu Tulai, Jan Angermeier, Gökce Taban
article en

Abstract

Abstract Assuming that all theoretical texts are at least intentionally aimed at introducing, defining, or relating concepts to one another, we propose a system for categorizing the components of such texts: we argue that on an abstract level, all parts of a theoretical text can be assigned to the categories theses, arguments, and notions. In the article, we explain how these categories were derived and how sthey can be used to create concept maps of theoretical texts, facilitating the analysis of the relation of such concepts in and across texts. We also report on an annotation workflow in which our theoretical concept is subjected to empirical testing and which serves as the basis for (semi-)automatic recognition of the three text parts and the creation of concept maps.

Digital Scholarship in the Humanities
University of Stuttgart (DE), University of Vienna (AT), University of Bucharest (RO)
Openalex Percentile: Top 87%
Natural Language Processing Techniques
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