Title: Diversity from the Topology of Citation Networks,
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.