The full BERTopic pipeline — transformer embeddings, UMAP, HDBSCAN density clustering, and c-TF-IDF topic representation — running entirely in R. No Python. No conda. No reticulate.
End-to-end walkthrough on 3,328 African research abstracts — embeddings, parameter sweep, topic fitting, and interactive visualisations.
Illustrated technical explainer: manifold hypothesis, fuzzy membership weights, SGD optimisation, and the effect of every parameter.
Core distances, mutual reachability, Borůvka MST, the condensed cluster tree, EOM extraction, and what every parameter controls.
install.packages("Rhobots")
library(Rhobots) rhobots_install() # restart R when prompted
rhobots_demo() # downloads Gutenberg books, fits a model, opens a plot
van der Pol, J.P.G. (2026). Rhobots: BERTopic-Style Topic Modeling Without Python. R package version 0.1.6. https://github.com/JPvdP/Rhobots