“马太效应”与科研网络中的择优依附

The Matthew Effect and Preferential Attachment in Scientific Networks

运用网络科学前沿方法,探寻现实网络幂律分布的起源与演化机制,是近年来国外马太效应研究的重要进路。物理学家Barabási和Albert于1999年提出择优依附机制:在网络扩张过程中,新入网节点倾向于依附已有诸多连结的节点。20年来,网络科学家通过择优依附描述现实系统中的优势积累过程。这些研究显示,科学界的马太效应稳健而普遍:科研合作网络遵循次线性择优依附,引证网络遵循超线性择优依附。如今,马太效应与择优依附已彼此相连、密不可分,然而在国内依然亟待学者扩展、深入和充实。

It is an important approach to explore the origin and evolution mechanism of power law distribution in real-world networks by using the frontier methods of network science.In 1999,physicists Barabási and Albert proposed the preferential attachment mechanism:In the process of network expansion,new nodes attach preferentially to sites that are already well connected.For 20 years,network scientists have measured preferential attachment to describe the process of cumulative accumulation in real systems.These studies show that the Matthew effect is robust and widespread in scientific community:sublinear preferential attachment governs the growth of scientific collaboration networks;citation cumulation is governed by superlinear preferential attachment.Nowadays,Matthew effect and preferential attachment have been closely connected and inseparable,but it is still urgent for domestic scholars to expand,deepen and enrich.