Argument mining for organizational research: a computer-aided analysis of organizational talk

Fedtke, Cornelia; Wiedemann, Gregor; Besio, Cristina

doi:10.1177/10944281261453948

Argument mining for organizational research: a computer-aided analysis of organizational talk

Publication date

2026-07-01

Document type

Forschungsartikel

Author

Fedtke, Cornelia

Wiedemann, Gregor

Besio, Cristina

Organisational unit

Soziologie mit dem Schwerpunkt Organisationssoziologie

DOI

10.1177/10944281261453948

URI

https://openhsu.ub.hsu-hh.de/handle/10.24405/24276

Scopus ID

2-s2.0-105043556646

Publisher

SAGE Publications

Series or journal

Organizational Research Methods

ISSN

1094-4281

Peer-reviewed

✅

Part of the university bibliography

✅

Language

English

Keyword

argument mining

natural language processing

organizational talk

organization–environment relationship

social media

Abstract

Argument mining—the automatic identification, classification, and linking of argumentative text—has been studied in natural language processing (NLP) for more than a decade. Despite its claimed potential for applications in legal, political, and social contexts, it remained largely unexplored in organizational research. This article introduces aspect-based argument mining (ABAM) as a methodical innovation for studying how organizations justify decisions, construct legitimacy, and relate to their environments through communicative acts. By scaling up the analysis of argumentative structures beyond the limits of small-scale, qualitative studies, ABAM enables the recognition and systematic analysis of argumentation patterns in large text corpora that were hardly detectable with previous (computational) approaches. The potential is demonstrated by a longitudinal case study of Twitter debates on nuclear energy in Germany, revealing how shifting societal values—particularly the reframing of nuclear energy from a safety to a climate issue—produced growing misalignments between organizational talk of a political party organization and its social media environment.

Description

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/).

Version

Online first

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