activity
20172022
most citedPageRank centrality and algorithms for weighted, directed networks with applications to World Input-Output Tables

5 citations · 12 across the 11 of their papers we have counts for

collaborators

13 papers

physics.soc-ph20221 cited

Preferential Attachment with Reciprocity: Properties and Estimation

Daniel Cirkovic, Tiandong Wang, Sidney Resnick

Reciprocity in social networks helps understand information exchange between two individuals, and indicates interaction patterns between pairs of users. A recent study indicates th…

stat.CO2022

An Efficient Algorithm for Generating Directed Networks with Predetermined Assortativity Measures

Tiandong Wang, Jun Yan, Yelie Yuan +1

Assortativity coefficients are important metrics to analyze both directed and undirected networks. In general, it is not guaranteed that the fitted model will always agree with the…

physics.soc-ph20211 cited

Asymptotic Dependence of In- and Out-Degrees in a Preferential Attachment Model with Reciprocity

Tiandong Wang, Sidney I. Resnick

Reciprocity characterizes the information exchange between users in a network, and some empirical studies have revealed that social networks have a high proportion of reciprocal ed…

math.ST2021

Asymptotic Behavior of Common Connections in Sparse Random Networks

Bikramjit Das, Tiandong Wang, Gengling Dai

Random network models generated using sparse exchangeable graphs have provided a mechanism to study a wide variety of complex real-life networks. In particular, these models help w…

physics.soc-ph20215 cited

PageRank centrality and algorithms for weighted, directed networks with applications to World Input-Output Tables

Panpan Zhang, Tiandong Wang, Jun Yan

PageRank (PR) is a fundamental tool for assessing the relative importance of the nodes in a network. In this paper, we propose a measure, weighted PageRank (WPR), extended from the…

physics.soc-ph2021

Measuring Reciprocity in a Directed Preferential Attachment Network

Tiandong Wang, Sidney Resnick

Empirical studies show that online social networks have not only in- and out-degree distributions with Pareto-like tails but also a high proportion of reciprocal edges. A classical…