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Zhongzhi Zhang - IEEE Xplore Author Profile

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We study resistance eccentricity, a fundamental metric in network science for measuring the structural significance of a node. For a node in a graph, the resistance eccentricity is its maximum resistance distance to all other nodes. Fast computation of resistance eccentricity for a given subset of nodes is essential for a wide range of applications. However, a naive computation, requiring the pseu...Show More
A signed graph offers richer information than an unsigned graph, since it describes both collaborative and competitive relationships in social networks. In this paper, we study opinion dynamics on a signed graph, based on the Friedkin-Johnsen model. We first interpret the equilibrium opinion in terms of a defined random walk on an augmented signed graph, by representing the equilibrium opinion of ...Show More
The formation of opinions is fundamentally a network-based process, where the opinions of individuals in a social network exchange, evolve, and eventually converge towards a specific distribution. However, this dynamic process may be susceptible to manipulation by adversarial entities, who aim to maliciously influence the opinion formulation. The adversary may engage in extensive influence campaig...Show More
Opinion dynamics is a central subject of computational social science, and various models have been developed to understand the evolution and formulation of opinions. Existing models mainly focus on opinion dynamics on graphs that only capture pairwise interactions between agents. In this article, we extend the popular Friedkin–Johnsen model for opinion dynamics on graphs to hypergraphs, which des...Show More
Critical nodes in networks are extremely vulnerable to malicious attacks to trigger negative cascading events such as the spread of misinformation and diseases. Therefore, effective moderation of critical nodes is very vital for mitigating the potential damages caused by such malicious diffusions. The current moderation methods are computationally expensive. Furthermore, they disregard the fundame...Show More
The function or performance of a network is strongly dependent on its robustness, which quantifies the ability of the network to continue functioning under perturbations. While a wide variety of robustness metrics have been proposed, they have their respective limitations. In this paper, we propose to use the forest index as a measure of network robustness, which overcomes the deficiencies of exis...Show More
We study second-order consensus dynamics with random additive disturbances. To quantify the robustness of these networks, we investigate three different performance measures: the steady-state variance of pairwise differences between vertex states, the steady-state variance of the deviation of each vertex state from the average, and the total steady-state variance of the system. We show that these ...Show More
Centrality metrics are one of the most fundamental tools in social network analysis and network science, and various measures for evaluating node importance metrics have been devised. However, the crucial issue of testing the discriminating power of different centrality measures is still open. In this article, we propose to assess the discriminating power of node centrality measures by using the n...Show More
A striking discovery in the field of network science is that the majority of real networked systems have some universal structural properties. In general, they are simultaneously sparse, scale-free, small-world, and loopy. In this article, we investigate the second-order consensus of dynamic networks with such universal structures subject to white noise at vertices. We focus on the network coheren...Show More
It has been recently established that for second-order consensus dynamics with additive noise, the performance measures, including the vertex coherence and network coherence defined, respectively, as the steady-state variance of the deviation of each vertex state from the average and the average steady-state variance of the system, are closely related to the biharmonic distances. However, direct c...Show More
We study diffusion and consensus dynamics in a network of networks model. In this model, there is a collection of subnetworks, connected to one another using a small number of links. We consider a setting where the links between networks have small weights, or are used less frequently than links within each subnetwork. Using spectral perturbation theory, we analyze the diffusion rate and convergen...Show More
The issue of opinion sharing and formation has received considerable attention in the academic literature, and a few models have been proposed to study this problem. However, existing models are limited to the interactions among nearest neighbors, ignoring those second, third, and higher-order neighbors, despite the fact that higher-order interactions occur frequently in real social networks. In t...Show More
We study the problem of maximizing the number of spanning trees in a connected graph with n vertices and m edges, by adding at most k edges from a given set of q candidate edges, a problem that has applications in many domains. We give both algorithmic and hardness results for this problem: 1) We give a greedy algorithm that obtains an approximation ratio of (1 - 1/e - ∈) in the exponent of the nu...Show More
The vast majority of real-world networks are scale-free, loopy, and sparse, with a power-law degree distribution and a constant average degree. In this paper, we study first-order consensus dynamics in binary scale-free networks, where vertices are subject to white noise. We focus on the coherence of networks characterized in terms of the H2-norm, which quantifies how closely the agents track the ...Show More
Ranking the relative importance of nodes is a fundamental issue in network science, especially in the analysis of social and information networks. A variety of importance metrics and related algorithms have been proposed. However, these previous measures either do not apply to disconnected networks or have some weakness when applied to disconnected networks. In this paper, we use forest distance t...Show More
Mean hitting time for random walks on a network, defined as the average of hitting times over all possible pairs of nodes, has found a large variety of applications in many areas. In this paper, we first prove that among all N-node networks, the complete graph has the minimum mean hitting time N - 1, which scales linearly with network size. We then study a random walk mobility model with location ...Show More
We study the performance of leader-follower noisy consensus networks and, in particular, the relationship between this performance and the locations of the leader nodes. Two types of dynamics are considered: 1) noise-free leaders, in which leaders dictate the trajectory exactly and followers are subject to external disturbances and 2) noise-corrupted leaders, in which both leaders and followers ar...Show More
The eigenvalues of a graph present a wide range of applications in structural and dynamical aspects of the graph. Determining and analyzing spectra of a graph has been an important and exciting research topic in recent years. In this paper, we study the spectra and their applications for extended Sierpiński graphs, which are closely related to WK-recursive networks that are widely used in the desi...Show More
The hierarchical graphs and Sierpiński graphs are constructed iteratively, which have the same number of vertices and edges at any iteration, but exhibit quite different structural properties: the hierarchical graphs are nonfractal and small-world, while the Sierpiński graphs are fractal and “large-world.” Both graphs have found broad applications. In this paper, we study consensus problems in hie...Show More
We study the convergence rate of consensus algorithms in a Network of Networks model. In this model, there is a collection of networks, and these individual networks are connected to one another using a small number of links to form a composite graph. We consider a setting where the links between networks are costly to use, and therefore, are used less frequently than links within each network. We...Show More
We study second-order consensus dynamics with random additive disturbances. We focus on three different performance measures: the steady-state variance of pairwise differences between vertex states, the steady-state variance of the deviation of each vertex state from the average, and the total steady-state variance of the system. We show that these performance measures are closely related to the b...Show More
In this brief, we study first- and second-order consensus algorithms for the scale-free small-world Koch network, where vertices are subject to white noise. We focus on three cases of consensus schemes: (1) first-order leaderless algorithm; (2) first-order algorithm with a single leader; and (3) second-order leaderless algorithm. We are concerned with the coherence of the Koch network in the H2 no...Show More
We could get the epidemic threshold from continuous-time SIS model in small-world networks, but the steady value of spreading process shows a large difference with the simulations. To explain this difference, by introducing discrete-time SIS model, the steady value fit well with the simulations as γ <; 1. As β = γ = 1, both models could not explain the periodicity in the spreading process.Show More
Traffic fluctuation has so far been studied on unweighted networks. However, many real traffic systems are better represented and understood as weighted networks, where nodes and links are assigned some weight values representing their physical properties such as capacity and delay. Here, we introduce a general random diffusion (GRD) model to investigate the traffic fluctuations on weighted networ...Show More