The rapid technological advancements allowed the processing of different kinds of data to study real-world phenomena in recent times. Within this context, textual data emerged as a crucial resource in several domains, paving the way for new research questions. Nonetheless, many researchers lack the programming skills needed to effectively analyse textual data, creating a demand for user-friendly analysis tools. Languages such as R and Python provide powerful and open-access solutions, but researchers often face time and resource constraints to become fairly proficient. This paper introduces TALL (Text Analysis for All ), an R Shiny app encompassing a wide set of methods tailored for key text analysis tasks. Its aim is to address the needs of researchers, providing a versatile and general-purpose tool for text analysis and enabling them to extract valuable insights in a more viable and accessible manner.
TALL: A new Shiny app for Text Analysis
Michelangelo Misuraca;
2024-01-01
Abstract
The rapid technological advancements allowed the processing of different kinds of data to study real-world phenomena in recent times. Within this context, textual data emerged as a crucial resource in several domains, paving the way for new research questions. Nonetheless, many researchers lack the programming skills needed to effectively analyse textual data, creating a demand for user-friendly analysis tools. Languages such as R and Python provide powerful and open-access solutions, but researchers often face time and resource constraints to become fairly proficient. This paper introduces TALL (Text Analysis for All ), an R Shiny app encompassing a wide set of methods tailored for key text analysis tasks. Its aim is to address the needs of researchers, providing a versatile and general-purpose tool for text analysis and enabling them to extract valuable insights in a more viable and accessible manner.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.