SportMiner - Text Mining and Topic Modeling for Sport Science Literature
A comprehensive toolkit for mining, analyzing, and
visualizing scientific literature in sport science domains.
Provides functions for retrieving abstracts from 'Scopus',
preprocessing text data, performing advanced topic modeling
using Latent Dirichlet Allocation ('LDA'), Structural Topic
Models ('STM'), and Correlated Topic Models ('CTM'), and
creating publication-ready visualizations including keyword
co-occurrence networks and topic trends. For methodological
details see Blei et al. (2003)
<doi:10.1162/jmlr.2003.3.4-5.993> for 'LDA', Roberts et al.
(2014) <doi:10.1111/ajps.12103> for 'STM', and Blei and
Lafferty (2007) <doi:10.1214/07-AOAS114> for 'CTM'.
