Diversity from the Topology of Citation Networks (1802.06015v1)

Abstract: We study transitivity in directed acyclic graphs and its usefulness in capturing nodes that act as bridges between more densely interconnected parts in such type of network. In transitively reduced citation networks degree centrality could be used as a measure of interdisciplinarity or diversity. We study the measure's ability to capture "diverse" nodes in random directed acyclic graphs and citation networks. We show that transitively reduced degree centrality is capable of capturing "diverse" nodes, thus this measure could be a timely alternative to text analysis techniques for retrieving papers, influential in a variety of research fields.