Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 538-554 |
| Number of pages | 17 |
| Journal | ISIS |
| Volume | 110 |
| Issue number | 3 |
| DOIs | |
| State | Published - Sep 1 2019 |
| Externally published | Yes |
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ASJC Scopus subject areas
- History
- Earth and Planetary Sciences (miscellaneous)
- History and Philosophy of Science
Cite this
Network analysis for the digital humanities : Principles, problems, extensions. / Painter, Deryc T.; Daniels, Bryan C.; Jost, Jürgen.
In: ISIS, Vol. 110, No. 3, 01.09.2019, p. 538-554.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Network analysis for the digital humanities
T2 - Principles, problems, extensions
AU - Painter, Deryc T.
AU - Daniels, Bryan C.
AU - Jost, Jürgen
PY - 2019/9/1
Y1 - 2019/9/1
N2 - 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.
AB - 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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U2 - 10.1086/705532
DO - 10.1086/705532
M3 - Article
AN - SCOPUS:85072049177
VL - 110
SP - 538
EP - 554
JO - Isis; an international review devoted to the history of science and its cultural influences
JF - Isis; an international review devoted to the history of science and its cultural influences
SN - 0021-1753
IS - 3
ER -