Coconut Libtool: Bridging Textual Analysis Gaps for Non-Programmers

TL;DR

Coconut Libtool is an accessible, web-based NLP application that enables non-programmers to perform advanced textual analysis tasks like topic modeling and visualization, promoting transparency and reproducibility in research.

Contribution

It introduces an open-source, user-friendly platform integrating multiple NLP techniques for non-programmers to analyze text data from various sources.

Findings

Supports analysis of data from bibliographic databases

Incorporates multiple NLP algorithms including LDA and BERTopic

Enhances accessibility and transparency in textual analysis

Abstract

In the era of big and ubiquitous data, professionals and students alike are finding themselves needing to perform a number of textual analysis tasks. Historically, the general lack of statistical expertise and programming skills has stopped many with humanities or social sciences backgrounds from performing and fully benefiting from such analyses. Thus, we introduce Coconut Libtool (www.coconut-libtool.com/), an open-source, web-based application that utilizes state-of-the-art natural language processing (NLP) technologies. Coconut Libtool analyzes text data from customized files and bibliographic databases such as Web of Science, Scopus, and Lens. Users can verify which functions can be performed with the data they have. Coconut Libtool deploys multiple algorithmic NLP techniques at the backend, including topic modeling (LDA, Biterm, and BERTopic algorithms), network graph visualization, keyword lemmatization, and sunburst visualization. Coconut Libtool is the people-first web application designed to be used by professionals, researchers, and students in the information sciences, digital humanities, and computational social sciences domains to promote transparency, reproducibility, accessibility, reciprocity, and responsibility in research practices.