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The study of the weak-ties phenomenon has a long and well documented history, research into the application of this social phenomenon has recently attracted increasing attention. However, further exploration of the reasons behind the weak-ties phenomenon is still challenging. Fortunately, data-driven network science provides a novel way with substantial explanatory power to analyze the causal mechanism behind social phenomenon. Inspired by this perspective, we propose an approach to further explore the driving factors behind the temporal weak-ties phenomenon. We find that the obvious intuition underlying the weak-ties phenomenon is incorrect, and often large numbers of unknown mutual friends associated with these weak ties is one of the key reason for the emergence of the weak-ties phenomenon. In particular, for example scientific collaborators with weak ties prefer to be involved in direct collaboration rather than share ideas with mutual colleagues -- there is a natural tendency to collapse short strong chains of connection.
Background: Controlling global epidemics in the real world and accelerating information propagation in the artificial world are of great significance, which have activated an upsurge in the studies on networked spreading dynamics. Lots of efforts hav
It is generally accepted that neighboring nodes in financial networks are negatively assorted with respect to the correlation between their degrees. This feature would play an important damping role in the market during downturns (periods of distress
There are different measures to classify a networks data set that, depending on the problem, have different success. For example, the resistance distance and eigenvector centrality measures have been successful in revealing ecological pathways and di
In this paper we apply techniques of complex network analysis to data sources representing public funding programs and discuss the importance of the considered indicators for program evaluation. Starting from the Open Data repository of the 2007-2013
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