Enclosed are the ancillary files for my paper, “Diachronic Trends in the Topic Distributions of Formal Epistemology Abstracts”, which I am submitting for consideration in the Synthese special issue “Metaphilosophy of Formal Methods”.

The ancillary files included are:

• A text file containing the full corpus of abstracts analyzed in the paper (abstracts.txt).

• A text file containing the twenty highest-probability words for each of the Level 1 topics (level1_topics.txt).

• A text file containing the twenty highest-probability words for each of the Level 2 topics (level2_topics.txt).

• A text file containing the Level 1 topic distribution for each abstract in the corpus (topic_dists_by_doc_L1.txt).

• A text file containing the Level 2 topic distribution for each abstract in the corpus (topic_dists_by_doc_L2.txt).

• A text file containing the publication years for each document (years.txt).

• A text file containing each unique publication year in the corpus (unique_years.txt).

• The Jupyter notebook used to produce the seven text files listed above (Code.ipynb).

• The code base for the SBM inference function used in the Jupyter notebook above (sbmtm.py).

• An Excel file used to analyze the Level 1 and Level 2 topic distributions, producing annual salience data and the two tables containing in the paper (data_analysis.xls).

• A text file containing compiled annual salience data for each Level 1 topic (salience_data_L1.txt).

• A text file containing compiled annual salience data for each Level 1 topic (salience_data_L2.txt).

• A text file containing the years for which salience data was analyzed (years_for_charts.txt).

• A text file containing the total number of abstracts for each year (year_counts.txt).

• The Jupyter notebook used to produce the charts in the paper using the four text files listed above (Chart_Generator.ipynb).