title: Tie strength distribution in scientific collaboration networks.
abstract: Science is increasingly dominated by teams. Understanding patterns of scientific collaboration and their impacts on the productivity and evolution of disciplines is crucial to understand scientific processes. Electronic bibliography offers a unique opportunity to map and investigate the nature of scientific collaboration. Recent studies have demonstrated a counterintuitive organizational pattern of scientific collaboration networks: densely interconnected local clusters consist of weak ties, whereas strong ties play the role of connecting different clusters. This pattern contrasts itself from many other types of networks where strong ties form communities while weak ties connect different communities. Although there are many models for collaboration networks, no model reproduces this pattern. In this paper, we present an evolution model of collaboration networks, which reproduces many properties of real-world collaboration networks, including the organization of tie strengths, skewed degree and weight distribution, high clustering, and assortative mixing.
authors.affiliation: Center for Complex Networks and Systems Research, School of Informatics and Computing, Indiana University, Bloomington, Indiana, USA.
authors.forename: Qing
authors.initials: Q
authors.lastname: Ke
authors.affiliation: Center for Complex Networks and Systems Research, School of Informatics and Computing, Indiana University, Bloomington, Indiana, USA.
authors.forename: Yong-Yeol
authors.initials: YY
authors.lastname: Ahn
mesh_terms: D001634:Bibliographies as Topic; D016000:Cluster Analysis; D003198:Computer Simulation; D003299:Cooperative Behavior; D008962:Models, Theoretical; D010825:Physics; D012106:Research