Causal Language Detection using Text-Document Features: Methodology and Insights from 10 Years of Gut Microbiome Research
This study develops and validates an automated L1-regularized logistic regression model using TF-IDF features to detect causal language in scientific abstracts, applying it to a decade of gut microbiome research to reveal significant temporal and thematic heterogeneity in how causal claims are framed.