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Hi All,

https://urldefense.proofpoint.com/v2/url?u=https-3A__www.sciencedirect.com_science_article_pii_S0378437119306375-3Fvia-253Dihub&d=DwIDaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=u31JdgdUWvOjhdwqn0S3KduhDeEKo2tIkUKR_5_qrdM&s=tnlfm8_kaZS73wOh-rIeYbI2YM1z5oxbmGPNMPrJb1I&e=

Many network researchers use intuitive or basic definitions when 
discussing the importance of strong and weak links and their roles. 
Others use an approach best described as “if not strong, then weak” to 
determine the strengths and weaknesses of individual links, thus 
deemphasizing hierarchical network structures that allow links to 
express different strength levels. Here we describe our proposal for an 
identification algorithm for determining link types at multiple network 
hierarchy levels based on the common neighbor concept plus statistical 
factors such as bond links, kth-layer local bridges, global bridges, and 
silk links—all generated during long-term network development and 
evolution processes. Two sets of networks were used to validate our 
proposed algorithm, one consisting of 16 networks employed in multiple 
past studies, and one consisting of two types of one-dimensional 
small-world networks expressing different random rewiring or shortcut 
addition probabilities. Two applications with potential for 
developmental contributions are demonstrated: a network fingerprint 
analysis framework, and a hierarchical network community partition method.


All best,


Chung-Yuan Huang



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