Noichl, Maximilian (2019) Modeling the Structure of Recent Philosophy. [Preprint]

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Abstract

This paper presents an approach of unsupervised learning of clusters from a citation database, and applies it to a large corpus of articles in philosophy to give an account of the structure of the discipline. Following a list of journals from the PhilPapers-archive, 68152 records were downloaded from the Reuters Web Of Science-Database. Their citation data was processed using dimensionality reduction and clustering. The resulting clusters were identified, and the results are graphically represented. They suggest that the division of analytic and Continental philosophy in the considered timespan is overstated; that analytical, in contrast to Continental philosophy does not form a coherent group in recent philosophy; and that metaphors about the disciplinary structure should focus on the coherence and interconnectedness of a multitude of smaller and larger subfields.

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Item Type:	Preprint
Creators:	Creators Email ORCID Noichl, Maximilian noichlmax@hotmail.co.uk 0000-0003-4518-0837
Subjects:	General Issues > Computer Simulation General Issues > History of Philosophy of Science Specific Sciences > Artificial Intelligence > Machine Learning
Depositing User:	Maximilian Noichl
Date Deposited:	02 Oct 2019 15:16
Last Modified:	02 Oct 2019 15:16
Item ID:	16470
Subjects:	General Issues > Computer Simulation General Issues > History of Philosophy of Science Specific Sciences > Artificial Intelligence > Machine Learning
Date:	4 September 2019
URI:	https://philsci-archive.pitt.edu/id/eprint/16470

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