In: Journal of Informetrics, 2016, vol. 10, no. 4, p. 1207–1223
Citations between scientific papers and related bibliometric indices, such as the h- index for authors and the impact factor for journals, are being increasingly used – often in controversial ways – as quantitative tools for research evaluation. Yet, a fundamental research question remains still open: to which extent do quantitative metrics capture the significance of scientific works? We...
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In: Scientific Reports, 2016, vol. 6, p. 34218
Understanding the behavior of users in online systems is of essential importance for sociology, system design, e-commerce, and beyond. Most existing models assume that individuals in diverse systems, ranging from social networks to e-commerce platforms, tend to what is already popular. We propose a statistical time-aware framework to identify the users who differ from the usual behavior by...
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In: Physics Letters A, 2016, vol. 380, no. 34, p. 2608–2614
There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model...
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In: Chaos: An Interdisciplinary Journal of Nonlinear Science, 2016, vol. 26, no. 6, p. 63108
Accurate identification of effective epidemic threshold is essential for understanding epidemic dynamics on complex networks. In this paper, we systematically study how the recovery rate affects the susceptible-infected-removed spreading dynamics on complex networks, where synchronous and asynchronous updating processes are taken into account. We derive the theoretical effective epidemic...
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In: Physica A: Statistical Mechanics and its Applications, 2016, vol. 460, p. 254–269
Numerical analysis of data from international trade and ecological networks has shown that the non-linear fitness–complexity metric is the best candidate to rank nodes by importance in bipartite networks that exhibit a nested structure. Despite its relevance for real networks, the mathematical properties of the metric and its variants remain largely unexplored. Here, we perform an analytic...
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In: Physica A: Statistical Mechanics and its Applications, 2016, vol. 444, p. 397–402
Bipartite matching problems emerge in many human social phenomena. In this paper, we study the ground state of the Gale–Shapley model, which is the most popular bipartite matching model. We apply the Kuhn–Munkres algorithm to compute the numerical ground state of the model. For the first time, we obtain the number of blocking pairs which is a measure of the system instability. We also show...
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In: Scientific Reports, 2015, vol. 5, p. 16181
PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm’s efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank’s...
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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: Physics Reports, 2015, vol. 552, p. 1–25
Demand outstrips available resources in most situations, which gives rise to competition, interaction and learning. In this article, we review a broad spectrum of multi-agent models of competition (El Farol Bar problem, Minority Game, Kolkata Paise Restaurant problem, Stable marriage problem, Parking space problem and others) and the methods used to understand them analytically. We emphasize the...
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In: Physica A: Statistical Mechanics and its Applications, 2015, vol. 436, p. 216–223
As a fundamental problem in many different fields, link prediction aims to estimate the likelihood of an existing link between two nodes based on the observed information. Since this problem is related to many applications ranging from uncovering missing data to predicting the evolution of networks, link prediction has been intensively investigated recently and many methods have been proposed so...
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