Computational Scientometric Modeling of E-book Usability Research and Knowledge Evolution
TL;DR
A hierarchical computational model of knowledge evolution is proposed, demonstrating the effectiveness of algorithmic citation analysis in mapping intellectual structures and offering insights into the future evolution of interactive reading design and related computational humanities fields.
Abstract
This study employs computational scientometric modeling to analyze the citation network of the seminal work Usability Evaluation of E-books, addressing the lack of quantitative understanding of how interdisciplinary knowledge evolves in interactive reading design and human–computer interaction. Using bibliometric data from Web of Science and Scopus, 135 citing publications were retrieved and processed through a data-driven citation-tracking algorithm. CiteSpace was utilized to generate dynamic knowledge maps integrating network topology, thematic clustering, and temporal modeling. The analysis reveals a hierarchical and concentric knowledge structure that evolved through three distinct stages: a technology-driven emergence phase (2009–2012), an application expansion phase (2013–2017), and a human-centered convergence phase (2018–present). Bridging nodes such as “visual fatigue” and “human–computer interaction” computationally link previously isolated research clusters, illustrating the mechanisms of interdisciplinary integration. The findings propose a hierarchical computational model of knowledge evolution, demonstrating the effectiveness of algorithmic citation analysis in mapping intellectual structures. This work provides a reproducible methodological framework for analyzing scholarly influence and knowledge development, offering insights into the future evolution of interactive reading design and related computational humanities fields.