Searching for coherence in a fragmented field: Temporal and keywords network analysis in political science

Dmitry G. Zaytsev, Valentina V. Kuskova, Gregory S. Khvatsky and Anna A. Sokol

Network Science, 2023, vol. 11, issue 1, 113-142

Abstract: In this paper, we answer the multiple calls for systematic analysis of paradigms and subdisciplines in political science—the search for coherence within a fragmented field. We collected a large dataset of over seven hundred thousand writings in political science from Web of Science since 1946. We found at least two waves of political science development, from behaviorism to new institutionalism. Political science appeared to be more fragmented than literature suggests—instead of ten subdisciplines, we found 66 islands. However, despite fragmentation, there is also a tendency for integration in contemporary political science, as revealed by co-existence of several paradigms and coherent and interconnected topics of the “canon of political science,” as revealed by the core-periphery structure of topic networks. This was the first large-scale investigation of the entire political science field, possibly due to newly developed methods of bibliometric network analysis: temporal bibliometric analysis and island methods of clustering. Methodological contribution of this work to network science is evaluation of islands method of network clustering against a hierarchical cluster analysis for its ability to remove misleading information, allowing for a more meaningful clustering of large weighted networks.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:cup:netsci:v:11:y:2023:i:1:p:113-142_6

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