Designing a Web Application for Text Analysis

This paper explores and presents the development of the frontend of a web application that deals with quantitative text analysis. Inspired by an existing desktop application, this project transfers and enhances these functionalities into a web environment, highlighting the significance and flexibility of the web environment. The technologies used for developing the frontend of the application, including the React framework, Chakra UI, and Charts.js, are reviewed. These technologies are crucial in shaping the user experience and functionality of the application. Key concepts used in the application for text analysis are described, such as tokenization, frequency tables, entropy, Shannon’s equitability, and Zipf’s distribution. The ultimate aim is to develop a web application that allows for diverse text analyses and can be easily upgraded with new functionalities, which is essential in the dynamic field of NLP. Such a platform enables users to avoid the complexities associated with software installation and maintenance, making the tool more accessible and practical for a wide range of users.