Scientific articles have semantic contents that are usually quite specific to their disciplinary origins. To characterize such semantic contents, topic-modeling algorithms make it possible to identify topics that run throughout corpora. However, they remain limited when it comes to investigating the extent to which topics are jointly used together in specific documents and form particular associative patterns. Here, we propose to characterize such patterns through the identification of “topic associative rules” that describe how topics are associated within given sets of documents. As a case study, we use a corpus from a subfield of the humanities—the philosophy of science—consisting of the complete full-text content of one of its main journals: Philosophy of Science. On the basis of a pre-existing topic modeling, we develop a methodology with which we infer a set of 96 topic associative rules that characterize specific types of articles depending on how these articles combine topics in peculiar patterns. Such rules offer a finer-grained window onto the semantic content of the corpus and can be interpreted as “topical recipes” for distinct types of philosophy of science articles. Examining rule networks and rule predictive success for different article types, we find a positive correlation between topological features of rule networks (connectivity) and the reliability of rule predictions (as summarized by the F-measure). Topic associative rules thereby not only contribute to characterizing the semantic contents of corpora at a finer granularity than topic modeling, but may also help to classify documents or identify document types, for instance to improve natural language generation processes.
Topic associative rule network: http://shiny.initiativesnumeriques.org/philosci_network/
Cite as: Malaterre, Christophe, Jean-François Chartier, Francis Lareau (under review) « The recipes of Philosophy of Science: Characterizing the semantic structure of corpora by means of topic associative rules ».
Acknowledgements: We are grateful to JSTOR for kindly providing access to the full-text corpus of Philosophy of Science. We thank Jonathan St-Onge for help with some graphics as well as the CIRST/BIN for hosting the visualization interface. We also thank the audiences of the 2019 Digital History and Philosophy of Science colloquium at UQAM, Montréal, and of the 2020 Corpus Fortnight | X-Phi Conference organized by the Australasian Experimental Philosophy Group where this work was initially presented. The manuscript benefited from the comments and suggestions of two reviewers for PLOS ONE. CM acknowledges support from Canada Foundation for Innovation 34555 and Canada Research Chairs CRC-950-230795. FL acknowledges funding from the Fonds de recherche du Québec – Société et culture FRQSC-276470. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.