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20112022
most citedWhen to look at a noisy Markov chain in sequential decision making if measurements are costly?

6 citations · 26 across the 23 of their papers we have counts for

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cs.SI20211 cited

Controlling Segregation in Social Network Dynamics as an Edge Formation Game

Rui Luo, Buddhika Nettasinghe, Vikram Krishnamurthy

This paper studies controlling segregation in social networks via exogenous incentives. We construct an edge formation game on a directed graph. A user (node) chooses the probabili…

cs.SI2021

A Directed, Bi-Populated Preferential Attachment Model with Applications to Analyzing the Glass Ceiling Effect

Buddhika Nettasinghe, Nazanin Alipourfard, Vikram Krishnamurthy +1

Preferential attachment, homophily and, their consequences such as the glass ceiling effect have been well-studied in the context of undirected networks. However, the lack of an in…

cs.SI20201 cited

Echo Chambers and Segregation in Social Networks: Markov Bridge Models and Estimation

Rui Luo, Buddhika Nettasinghe, Vikram Krishnamurthy

This paper deals with the modeling and estimation of the sociological phenomena called echo chambers and segregation in social networks. Specifically, we present a novel community-…

cs.SI2020

Controllability of Network Opinion in Erdos-Renyi Graphs using Sparse Control Inputs

Geethu Joseph, Buddhika Nettasinghe, Vikram Krishnamurthy +1

This paper considers a social network modeled as an Erdos Renyi random graph. Each individual in the network updates her opinion using the weighted average of the opinions of her n…

cs.SI2019

Maximum Likelihood Estimation of Power-law Degree Distributions via Friendship Paradox based Sampling

Buddhika Nettasinghe, Vikram Krishnamurthy

This paper considers the problem of estimating a power-law degree distribution of an undirected network using sampled data. Although power-law degree distributions are ubiquitous i…

cs.SI2019

Friendship Paradox Biases Perceptions in Directed Networks

Nazanin Alipourfard, Buddhika Nettasinghe, Andres Abeliuk +2

How popular a topic or an opinion appears to be in a network can be very different from its actual popularity. For example, in an online network of a social media platform, the num…