The rapid technological advancements in recent years allowed to process different kinds of data to study several real-world phenomena. Within this context, textual data has emerged as a crucial resource in numerous research domains, opening avenues for new research questions and insights. However, many researchers lack the necessary programming skills to effectively analyze textual data, creating a demand for user-friendly text analysis tools. While languages such as R and python provide powerful capabilities, researchers often face constraints in terms of time and resources required to become proficient in these languages. This paper introduces TAll - Text Analysis for All, an R Shiny app that includes a wide set of methodologies specifically tailored for various text analysis tasks. It aims to address the needs of researchers without extensive programming skills, providing a versatile and general-purpose tool for analyzing textual data. With TAll, researchers can leverage a wide range of text analysis techniques without the burden of extensive programming knowledge, enabling them to extract valuable insights from textual data in a more efficient and accessible manner.

TAll: A New Shiny App of Text Analysis for All / Aria, Massimo; Cuccurullo, Corrado; D’Aniello, Luca; Misuraca, Michelangelo; Spano, Maria. - (2023), pp. 476-479. (Intervento presentato al convegno The Ninth Italian Conference on Computational Linguistics (CLiC-it 2023)).

TAll: A New Shiny App of Text Analysis for All

Massimo Aria;Corrado Cuccurullo;Luca D’Aniello;Michelangelo Misuraca;Maria Spano
2023

Abstract

The rapid technological advancements in recent years allowed to process different kinds of data to study several real-world phenomena. Within this context, textual data has emerged as a crucial resource in numerous research domains, opening avenues for new research questions and insights. However, many researchers lack the necessary programming skills to effectively analyze textual data, creating a demand for user-friendly text analysis tools. While languages such as R and python provide powerful capabilities, researchers often face constraints in terms of time and resources required to become proficient in these languages. This paper introduces TAll - Text Analysis for All, an R Shiny app that includes a wide set of methodologies specifically tailored for various text analysis tasks. It aims to address the needs of researchers without extensive programming skills, providing a versatile and general-purpose tool for analyzing textual data. With TAll, researchers can leverage a wide range of text analysis techniques without the burden of extensive programming knowledge, enabling them to extract valuable insights from textual data in a more efficient and accessible manner.
2023
979-12-550-0084-6
TAll: A New Shiny App of Text Analysis for All / Aria, Massimo; Cuccurullo, Corrado; D’Aniello, Luca; Misuraca, Michelangelo; Spano, Maria. - (2023), pp. 476-479. (Intervento presentato al convegno The Ninth Italian Conference on Computational Linguistics (CLiC-it 2023)).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/1013868
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