A Data-Driven Introduction to Authors, Readings, and Techniques in Visualization for the Digital Humanities.

Area of Science:

• Interdisciplinary studies bridging data visualization and digital humanities.
• Emerging field attracting researchers from computer science and humanities.

Background:

• The intersection of data visualization and digital humanities is a growing area of scholarly experimentation.
• Complexity in this field can be a barrier for new researchers.

Purpose of the Study:

• To provide an introductory, data-driven overview of visualization for digital humanities.
• To identify prominent themes, authors, and research opportunities within the field.

Main Methods:

• Constructed a representative dataset by analyzing citations from 300 core publications.
• Examined over 1900 referenced works to identify citation patterns and prominent authors.
• Analyzed paper keywords to determine significant themes and research gaps.

Main Results:

• Identified key citation networks and influential authors within visualization for digital humanities.
• Uncovered significant themes and emerging research trends through keyword analysis.
• Established a data-driven foundation for understanding the discipline's landscape.

Conclusions:

• This research facilitates engagement for scholars new to visualization in digital humanities.
• The findings offer insights into the current state and future directions of the field.
• Highlights the importance of data-driven approaches in interdisciplinary research.