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
Michelangelo Misuraca
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.


