Homophily and missing links in citation networks
Valerio Ciotti, Moreno Bonaventura, Vincenzo Nicosia, Pietro, Panzarasa, Vito Latora

TL;DR
This study investigates how homophily influences citation patterns in scientific literature, introduces a method to identify missing links between related papers, and assesses how different journals facilitate knowledge transfer.
Contribution
It presents a novel statistical validation method for measuring article similarity and uncovers missing citations, providing insights into barriers and facilitators of knowledge dissemination.
Findings
Citation probability increases with article similarity.
Highly related papers often have missing citations.
Wide visibility journals better facilitate knowledge transfer.
Abstract
Citation networks have been widely used to study the evolution of science through the lenses of the underlying patterns of knowledge flows among academic papers, authors, research sub-fields, and scientific journals. Here we focus on citation networks to cast light on the salience of homophily, namely the principle that similarity breeds connection, for knowledge transfer between papers. To this end, we assess the degree to which citations tend to occur between papers that are concerned with seemingly related topics or research problems. Drawing on a large data set of articles published in the journals of the American Physical Society between 1893 and 2009, we propose a novel method for measuring the similarity between articles through the statistical validation of the overlap between their bibliographies. Results suggest that the probability of a citation made by one article to another…
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