BOPIM: Bayesian Optimization for influence maximization on temporal networks
E Yanchenko - arXiv preprint arXiv:2308.04700, 2023 - arxiv.org
The goal of influence maximization (IM) is to select a small set of seed nodes which
maximize the spread of influence on a network. In this work, we propose BOPIM, a Bayesian …
maximize the spread of influence on a network. In this work, we propose BOPIM, a Bayesian …
Temporal Link Prediction in Social Networks Based on Agent Behavior Synchrony and a Cognitive Mechanism
Y Duan, M Nurek, Q Guan, R Michalski… - arXiv preprint arXiv …, 2024 - arxiv.org
Temporality, a crucial characteristic in the formation of social relationships, was used to
quantify the long-term time effects of networks for link prediction models, ignoring the …
quantify the long-term time effects of networks for link prediction models, ignoring the …
A generalized hypothesis test for community structure in networks
E Yanchenko, S Sengupta - Network Science, 2024 - cambridge.org
Researchers theorize that many real-world networks exhibit community structure where
within-community edges are more likely than between-community edges. While numerous …
within-community edges are more likely than between-community edges. While numerous …
TBCELF: Temporal Budget-Aware Influence Maximization
A Zahoor, IA Gillani, J Bashir - Proceedings of the 7th Joint International …, 2024 - dl.acm.org
Influence Maximization addresses the challenge of identifying a small group of
disseminators, known as seeds, essential for achieving maximal influence spread …
disseminators, known as seeds, essential for achieving maximal influence spread …
Fair vaccination strategies with influence maximization: a case study on COVID-19
N Neophytou - 2024 - papyrus.bib.umontreal.ca
During the Covid-19 pandemic, racial minorities and economically-disadvantaged groups
experienced heightened rates of infection, hospitalization and death in urban areas. This …
experienced heightened rates of infection, hospitalization and death in urban areas. This …
[PDF][PDF] On Prior Distributions for Scale Parameters in Hierarchical Models and Inference for Meso-scale Structures in Networks.
EK Yanchenko - 2023 - repository.lib.ncsu.edu
ABSTRACT YANCHENKO, ERIC KNOWLTON. On Prior Distributions for Scale Parameters
in Hierarchical Models and Inference for Meso-scale Structures in Networks.(Under the …
in Hierarchical Models and Inference for Meso-scale Structures in Networks.(Under the …