Dynamic opinion maximization in social networks
Opinion Maximization (OM) aims at determining a small set of influential individuals,
spreading the expected opinions of an object (eg, product or individual) to their neighbors …
spreading the expected opinions of an object (eg, product or individual) to their neighbors …
Reinforcement-learning-based dynamic opinion maximization framework in signed social networks
Dynamic opinion maximization (DOM) is a significant optimization issue, whose target is to
select some nodes in the network and prorogate the opinions of network nodes, and …
select some nodes in the network and prorogate the opinions of network nodes, and …
Opinion maximization through unknown influence power in social networks under weighted voter model
Opinion maximization in social networks is an optimization problem, which targets at
determining some influential individuals (ie, seed nodes), propagating the desired opinion to …
determining some influential individuals (ie, seed nodes), propagating the desired opinion to …
Bounds on the price of anarchy for a more general class of directed graphs in opinion formation games
In opinion formation games with directed graphs, a bounded price of anarchy is only known
for weighted Eulerian graphs. Thus, we bound the price of anarchy for a more general class …
for weighted Eulerian graphs. Thus, we bound the price of anarchy for a more general class …
Scalable equilibrium computation in multi-agent influence games on networks
We provide a polynomial-time, scalable algorithm for equilibrium computation in multi-agent
influence games on networks, extending work of Bindel, Kleinberg, and Oren (2015) from …
influence games on networks, extending work of Bindel, Kleinberg, and Oren (2015) from …
An effective scheme to address influence maximization for opinion formation in social networks
Influence maximization for opinion formation (IMOF) is an important problem in social
networks, which aims to select most influential nodes and obtains the maximal propagation …
networks, which aims to select most influential nodes and obtains the maximal propagation …
Misinformation as Information Pollution
A Kazemi, R Mihalcea - arxiv preprint arxiv:2306.12466, 2023 - arxiv.org
Social media feed algorithms are designed to optimize online social engagements for the
purpose of maximizing advertising profits, and therefore have an incentive to promote …
purpose of maximizing advertising profits, and therefore have an incentive to promote …
Mixed Integer Programming and LP Rounding for Opinion Maximization on Directed Acyclic Graphs
PA Chen, YW Cheng, YW Tseng - … & Their Applications X: Volume 1 …, 2022 - Springer
Gionis et al. have already proposed a greedy algorithm and some heuristics for the opinion
maximization problem. Unlike their approach, we adopt mathematical programming to solve …
maximization problem. Unlike their approach, we adopt mathematical programming to solve …
Opinion Optimization for Two Different Social Objectives: Combinatorial Algorithms and Linear Program Rounding.
PA Chen, YL Chen, W Lo - Journal of Information Science & …, 2024 - search.ebscohost.com
In this paper, we aim to optimize the two different social objectives of opinion optimization at
equilibrium by controlling some individuals. This is usually called" Stackelberg games", in …
equilibrium by controlling some individuals. This is usually called" Stackelberg games", in …
[PDF][PDF] Scalable Equilibrium Computation in Multi-agent Influence Games on Networks
M Hajiaghayi - Proceedings of the AAAI Conference on Artificial …, 2021 - par.nsf.gov
We provide a polynomial-time, scalable algorithm for equilibrium computation in multi-agent
influence games on networks, extending work of Bindel, Kleinberg, and Oren (2015) from …
influence games on networks, extending work of Bindel, Kleinberg, and Oren (2015) from …