The rise and fall of network stars: Analyzing 2.5 million graphs to reveal how high-degree vertices emerge over time
作者：
Highlights：
• We constructed the largest publicly available network evolution dataset to date, which contains 38,000 real-world networks and 2.5 million graphs.
• Links are most prevalent among vertices that join a network at a similar time.
• The rate that new vertices join a network is a central factor in molding a network’s topology.
• The emergence of network stars (high-degree vertices) is correlated with fast-growing networks.
• A novel flexible network-generation model based on large-scale real-world data is presented.
摘要
•We constructed the largest publicly available network evolution dataset to date, which contains 38,000 real-world networks and 2.5 million graphs.•Links are most prevalent among vertices that join a network at a similar time.•The rate that new vertices join a network is a central factor in molding a network’s topology.•The emergence of network stars (high-degree vertices) is correlated with fast-growing networks.•A novel flexible network-generation model based on large-scale real-world data is presented.
论文关键词：Data science,Network science,Big data,Network dynamics,Network datasets
论文评审过程：Received 14 October 2018, Revised 3 May 2019, Accepted 4 May 2019, Available online 16 May 2019, Version of Record 13 January 2020.
论文官网地址：https://doi.org/10.1016/j.ipm.2019.05.002
