TALL: Text analysis for all–an interactive R-shiny application for exploring, modeling, and visualizing textual data

Analyzing unstructured textual data is essential across disciplines, but often requires programming skills that many researchers lack. TALL ( Text Analysis for All ) is an interactive R -Shiny application that unifies data import, cleaning, pre-processing, statistical analysis, and visualization into a single tool. It supports tokenization, lemmatization and Part-of-Speech (PoS) tagging for analyses in multiple languages. It includes topic modeling, correspondence and cluster analysis, co-occurrence networks, polarity detection, word embedding and text summarization. Designed for accessibility and reproducibility, TALL enables non-programmers to perform advanced text analysis efficiently and effectively. This article outlines the architecture and functionalities, demonstrating its use through illustrative examples. • TALL democratizes text analysis through a code-free, interactive R-Shiny interface. • Supports 56 languages via 87 pre-trained models based on Universal Dependencies. • Integrates an AI assistant for natural-language interpretation of analytical results. • Unifies data import, NLP pre-processing, analysis, and visualization in one tool. • Open-source, FAIR-compliant, and reproducible.