Conceptual Mapping of Controversies

TL;DR

The paper tackles how to characterize and navigate controversies in online news by fusing Formal Concept Analysis with the economics of conventions to build conceptual maps from journal articles. It computes concept lattices to enable article navigation and uses ordinal data science to analyze controversy structure, demonstrated on electromobility across two journals. The work shows distinct journal-specific patterns (one simpler with bias towards certain conventions, the other more diverse) and proposes four navigation modes that offer transparent, multi-perspective access beyond traditional recommender systems. This framework supports evaluative discourse analysis and could inform more democratic, behaviorally aware news navigation, while acknowledging usability and context challenges in real-world deployment.

Abstract

With our work, we contribute towards a qualitative analysis of the discourse on controversies in online news media. For this, we employ Formal Concept Analysis and the economics of conventions to derive conceptual controversy maps. In our experiments, we analyze two maps from different news journals with methods from ordinal data science. We show how these methods can be used to assess the diversity, complexity and potential bias of controversies. In addition to that, we discuss how the diagrams of concept lattices can be used to navigate between news articles.

Figures (3)

• Figure 1: The scale on which we measure the conventions. C is the placeholder for the specific convention.
• Figure 2: Two complete greedy ordinal factorizations of the data sets analyzed in this work. In both cases, the first ordinal factor $F_1$ is the determinative factor and indicates the focus of the journal.
• Figure :