Article ID: CBB443684783

Network Analysis for the Digital Humanities: Principles, Problems, Extensions (2019)

unapi

Traditional historical scholarship struggles to keep up with the rapid pace of modern scientific publication trends. Even focusing on a particular scientific field, the rate of new publications far outpaces even the most studious historian’s research capacity. This essay summarizes an approach to this problem that uses computational techniques of network analysis. As a complement to close analysis of particular documents, network analysis can give a large-scale perspective on the history of science, identifying relational patterns across a vast number of documents that might otherwise require an entire career to digest. To demonstrate the power of the approach, the essay applies network theory to a corpus of publications in evolutionary medicine. Four distinct networks, including those focused on authors, keywords, and citations, quickly unearth a range of relevant historical information. The essay illustrates how interpretable historical conclusions are drawn from a variety of quantitative metrics. The aim is to provide an overview of network techniques for historians looking to add robust network analysis to their research repertoire.

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Authors & Contributors
Damerow, Julia
Plutniak, Sébastien
Gibson, Abraham Hill
Laubichler, Manfred Dietrich
Guldi, Jo
Erin Bottino
Journals
Isis: International Review Devoted to the History of Science and Its Cultural Influences
ARCS Network Analysis for Social Sciences
Technology and Culture
Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences
Physis: Rivista Internazionale di Storia della Scienza
Nova Acta Paracelsica: Jahrbuch der Schweizerischen Paracelsus-Gesellschaft
Publishers
Virginia Polytechnic Institute
Arizona State University
Oxford University Press
MIT Press
Indiana University
Concepts
Digital humanities
Computational methods
Text mining
Historiography
Data collection; methods
Data analysis
People
Gardin, Jean-Claude
Garelli, Paul
Paracelsus, Theophrast von Hohenheim
Darwin, Charles Robert
Time Periods
21st century
20th century, late
19th century
Places
River Shannon
Assyria
United States
Europe
Asia
Great Britain
Institutions
Great Britain. Parliament
National Library of Medicine (U.S.)
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