In: Chaos: An Interdisciplinary Journal of Nonlinear Science, 2015, vol. 25, no. 10, p. 103102
Individuals are always limited by some inelastic resources, such as time and energy, which restrict them to dedicate to social interaction and limit their contact capacities. Contact capacity plays an important role in dynamics of social contagions, which so far has eluded theoretical analysis. In this paper, we first propose a non-Markovian model to understand the effects of contact capacity on...
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In: PLoS ONE, 2013, vol. 8, no. 2, p. e55437
Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. This article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and...
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In: Physica A: Statistical Mechanics and its Applications, 2012, vol. 139, no. 22, p. 5769–5778
To evaluate the performance of prediction of missing links, the known data are randomly divided into two parts, the training set and the probe set. We argue that this straightforward and standard method may lead to terrible bias, since in real biological and information networks, missing links are more likely to be links connecting low-degree nodes. We therefore study how to uncover missing links...
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In: Physica A: Statistical Mechanics and its Applications, 2011, vol. 390, no. 23-24, p. 4486-4493
The explosive growth of information asks for advanced information filtering techniques to solve the so-called information overload problem. A promising way is the recommender system which analyzes the historical records of users’ activities and accordingly provides personalized recommendations. Most recommender systems can be represented by user-object bipartite networks where users can...
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