  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.
