{ "_id": "6a3ffc6fa319ef94144a2daa", "Package": "faSTM", "Title": "Fast Structural Topic Models", "Version": "0.0.0.9000", "Authors@R": "c(\nperson(\"Neal\", \"Caren\", email = \"neal.caren@unc.edu\", role = c(\"aut\", \"cre\")),\nperson(\"Margaret\", \"Roberts\", role = \"cph\",\ncomment = \"author of stm; inspection formulas in inspect.R adapted from stm (MIT)\"),\nperson(\"Brandon\", \"Stewart\", role = \"cph\", comment = \"author of stm (MIT)\"),\nperson(\"Dustin\", \"Tingley\", role = \"cph\", comment = \"author of stm (MIT)\"))", "Description": "A modern implementation of the Structural Topic Model.\nfaSTM fits the logistic-normal STM (with prevalence and content\ncovariates) via a multithreaded Rust core, with an opt-in\nstochastic-variational path for large corpora. It is\nself-contained: text preparation is read from 'quanteda' or\n'tidytext' objects, model inspection (labelTopics with\nFREX/lift/score, findThoughts, semantic coherence, exclusivity,\ntopic correlations) and an estimateEffect()\n(method-of-composition posterior propagation) are built in. 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