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• W2049406449 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." @default.
• W2049406449 created "2016-06-24" @default.
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• W2049406449 date "2014-09-11" @default.
• W2049406449 modified "2023-09-24" @default.
• W2049406449 title "Tie strength distribution in scientific collaboration networks" @default.
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• W2049406449 doi "https://doi.org/10.1103/physreve.90.032804" @default.
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