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.
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Notes
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We may note that we do not claim that the selection is representative for both journals. For future, more extensive investigations we envision the use of attribute exploration [13] to cover all relevant types of articles. For this study we refrain from doing so due to the big expense in manually classifying articles in terms of their conventions and the limited access to the journal’s data source. We can also envision that the use of machine learning can help to speed up the classification process – with a potential loss of accuracy. Preliminary research in that direction has been conducted [32].
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Funding
This work was performed in the project FAIRDIENSTE which was funded by the German Federal Ministry of Education and Research (BMBF) in its program “Economical aspects of IT security and privacy” under grant number 16KIS1249K.
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Draude, C. et al. (2024). Conceptual Mapping of Controversies. In: Cabrera, I.P., Ferré, S., Obiedkov, S. (eds) Conceptual Knowledge Structures. CONCEPTS 2024. Lecture Notes in Computer Science(), vol 14914. Springer, Cham. https://doi.org/10.1007/978-3-031-67868-4_14
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