Exploring the Technical Knowledge Interaction of Global Digital Humanities: Three-decade Evidence from Bibliometric-based perspectives

2025-08-11

AI Summary

Existing digital humanities (DH) research predominantly relies on conventional bibliometrics, failing to uncover the underlying mechanisms linking technical methods and humanistic themes. Method: This paper introduces the novel concept of “Topic-Method Combinations” (TMCs) and proposes an integrative framework combining bibliometric analysis, BERTopic-based topic modeling, and multilayer network analysis to systematically trace the evolution of global DH knowledge structures from 1994 to 2023. An original TMC identification and dynamic tracking workflow enables interpretable characterization of method–theme couplings. Contribution/Results: The study uncovers three major technological trajectories and a disciplinary integration gradient within DH, moving beyond superficial associations. It provides the first explainable, fine-grained mapping of how computational tools co-evolve with humanistic inquiry. The proposed framework demonstrates strong cross-disciplinary transferability, offering a scalable paradigm for studying method–domain interplay in other interdisciplinary fields.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Data Mining & Knowledge Management: Linked Open Data, Knowledge Graphs & KB Completion
• Humans and AI: Understanding People, Theories, Concepts and Methods

Application Category

• Web Mining and Content Analysis: Topic discovery and tracking
• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Graph Algorithms and Modeling for the Web: Graph neural networks and deep learning approaches for Web-related graphs

Abstract

Digital Humanities (DH) is an interdisciplinary field that integrates computational methods with humanities scholarship to investigate innovative topics. Each academic discipline follows a unique developmental path shaped by the topics researchers investigate and the methods they employ. With the help of bibliometric analysis, most of previous studies have examined DH across multiple dimensions such as research hotspots, co-author networks, and institutional rankings. However, these studies have often been limited in their ability to provide deep insights into the current state of technological advancements and topic development in DH. As a result, their conclusions tend to remain superficial or lack interpretability in understanding how methods and topics interrelate in the field. To address this gap, this study introduced a new concept of Topic-Method Composition (TMC), which refers to a hybrid knowledge structure generated by the co-occurrence of specific research topics and the corresponding method. Especially by analyzing the interaction between TMCs, we can see more clearly the intersection and integration of digital technology and humanistic subjects in DH. Moreover, this study developed a TMC-based workflow combining bibliometric analysis, topic modeling, and network analysis to analyze the development characteristics and patterns of research disciplines. By applying this workflow to large-scale bibliometric data, it enables a detailed view of the knowledge structures, providing a tool adaptable to other fields.

Problem

• Analyzing interaction between topics and methods in Digital Humanities
• Overcoming limitations in understanding DH technological advancements
• Developing a workflow to study knowledge structures in disciplines

Innovation

• Introduces Topic-Method Composition (TMC) concept
• Combines bibliometric analysis with topic modeling
• Uses network analysis for knowledge structure insights