learning-stm | Learning structural topic modeling using the stm R package | Topic Modeling library

learning-stm is a HTML library typically used in Artificial Intelligence, Topic Modeling applications. learning-stm has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

A Structural Topic Model is a general framework for topic modeling with document-level covariate information, which can improve inference and qualitative interpretability by affecting topical prevalence, topic content, or both (Roberts et al. 2016). The goal of the Structural Topic Model is to allow researchers to discover topics and estimate their relationships to document metadata where the outputs of the models can be used for hypothesis testing of these relationships. The stm R package implements the estimation algorithms for the model and includes tools for every stage of a standard workflow including model estimation, summary, and visualisation.