  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 work have demonstrated a counter-intuitive
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.
