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: Text analysis for all–an interactive R-shiny application for exploring, modeling, and visualizing textual data
Cuccurullo, Corrado;
2026
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


