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Modeling co-citation networks from historical records with R

appsOther research productkeyboard_double_arrow_right InteractiveResource 28 Jul 2022Publisher:ZenodoFunded by:EC | Cartesian Networks
Authors: Rossini, Paolo;

doi: 10.5281/zenodo.6948755 , 10.5281/zenodo.6924306 , 10.5281/zenodo.6924305

Modeling co-citation networks from historical records with R

Abstract

Co-citations can be very insightful when analyzed on a large scale. This tutorial, specifically devised for historians, offers a step-by-step guide for performing co-citation analysis with R. It is meant as a supplement to a research article currently under review. Acknowledgments I would like to thank Eugenio Petrovich for guiding me through the technicalities of co-citation analysis.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
0
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