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TALL - Text Analysis for ALL, an R Shiny app that includes a wide set ofmethodologies specifically tailored for various text analysis tasks. Itaims to address the needs of researchers without extensive programmingskills, providing a versatile and general-purpose tool for analyzingtextual data. With TALL, researchers can leverage a wide range of textanalysis techniques without the burden of extensive programmingknowledge, enabling them to extract valuable insights from textual datain a more efficient and accessible manner.

View tutorial

TALL can be installed in two ways, depending on whether you want thestable version or the latest development version.

You can install theofficial release of TALL from the ComprehensiveR Archive NetworkCRAN andupdated monthly.

if (!require("pak",quietly=TRUE)) install.packages("pak")pak::pkg_install("tall")

If you want access to the most recent features and updates not yetavailable on CRAN, you can install thedevelopment version directlyfromour GitHub repository with:

if (!require("pak",quietly=TRUE)) install.packages("pak")pak::pkg_install("massimoaria/tall")

Load the library with:

library("tall")

and then run TALL shiny app with:

tall()

In the age of information abundance, researchers across diversedisciplines are confronted with the formidable task of analyzingvoluminous textual data. Textual data, encompassing research articles,social media posts, customer reviews, and survey responses, harborsinvaluable insights that can propel knowledge advancement in variousfields, ranging from social sciences to healthcare and beyond.Researchers endeavor to analyze textual data to unveil patterns, discerntrends, extract meaningful information, and gain deeper understandingsof diverse phenomena. By leveraging sophisticated natural languageprocessing (NLP) techniques and machine learning algorithms, researcherscan delve into the semantic and syntactic structures of texts, performtopic detection, polarity detection, and text summarization, among otheranalyses. Additionally, the advent of digital platforms and theexponential growth of online content have generated unprecedentedvolumes of textual data that were previously inaccessible or challengingto acquire.

Researchers can harness the power of these textual resources to delveinto novel research questions, corroborate existing theories, andgenerate groundbreaking insights. Through the utilization ofcomputational tools and methodologies, researchers can efficientlyprocess and analyze expansive volumes of text, substantially reducingthe time and effort expended compared to manual analysis. Furthermore,there is a burgeoning recognition of the need for text analysis toolstailored to individuals who may not possess in-depth programmingexpertise. While programming languages like R and Python offer powerfulcapabilities for data analysis, not all researchers have the time orresources to acquire proficiency in these languages. To address thischallenge, a growing number of user-friendly text analysis tools haveemerged, providing researchers with a viable alternative to traditionalprogramming-based approaches. These tools empower researchers fromdiverse backgrounds to effectively process and analyze textual data,fostering a more inclusive research environment and democratizing accessto the transformative power of text analysis.

For researchers who lack programming skills, TALL offers a viablesolution, providing an intuitive interface that allow researchers tointeract with data and perform analyses without the need for extensiveprogramming knowledge.

TALL offers a comprehensive workflow for data cleaning, pre-processing,statistical analysis, and visualization of textual data, by combiningstate-of-the-art text analysis techniques into an R Shiny app.

First TALL seamlessly integrates the functionalities of a suite of Rpackages designed for NLP tasks with the user-friendly interface of webapplications through the Shiny package environment.

The TALL workflow streamlines the discovery and analysis of textual databy systematically processing and exploring its content. Thiscomprehensive framework empowers researchers with a versatile toolkitfor text analysis, enabling them to efficiently navigate and extractmeaningful insights from large volumes of textual data.

By leveraging the strengths of both R packages and Shiny’s interactiveweb interface, TALL provides a powerful and accessible platform forresearchers to conduct thorough the following workflow:

1. Import and Manipulation

2. Pre-processing and Cleaning

3. Statistical Text Analysis and Dynamic Visualization

• Massimo Aria

  • email:aria@unina.it

  • ORCID:https://orcid.org/0000-0002-8517-9411

• Corrado Cuccurullo

  • email:cuccurullocorrado@gmail.com

  • ORCID:https://orcid.org/0000-0002-7401-8575

• Luca D’Aniello

  • email:luca.daniello@unina.it

  • ORCID:https://orcid.org/0000-0003-1019-9212

• Maria Spano

  • email:maria.spano@unina.it

  • ORCID:https://orcid.org/0000-0002-3103-2342

• Michelangelo Misuraca

  • email:mmisuraca@unisa.it

  • ORCID:https://orcid.org/0000-0002-8794-966X

Massimo Aria

MIT License.

Copyright 2023 Massimo Aria

Permission is hereby granted, free of charge, to any person obtaining acopy of this software and associated documentation files (the“Software”), to deal in the Software without restriction, includingwithout limitation the rights to use, copy, modify, merge, publish,distribute, sublicense, and/or sell copies of the Software, and topermit persons to whom the Software is furnished to do so, subject tothe following conditions:

The above copyright notice and this permission notice shall be includedin all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESSOR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OFMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANYCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THESOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.