A survey on influence maximization in a social network
Given a social network with diffusion probabilities as edge weights and a positive integer k,
which k nodes should be chosen for initial injection of information to maximize the influence …
which k nodes should be chosen for initial injection of information to maximize the influence …
A new algorithm for positive influence maximization in signed networks
W Ju, L Chen, B Li, W Liu, J Sheng, Y Wang - Information Sciences, 2020 - Elsevier
With the rapid development of online social networks, the problem of influence maximization
(IM) has attracted much attention from researchers and has been applied in many areas …
(IM) has attracted much attention from researchers and has been applied in many areas …
Influence maximization in real-world closed social networks
In the last few years, many closed social networks such as WhatsAPP and WeChat have
emerged to cater for people's growing demand of privacy and independence. In a closed …
emerged to cater for people's growing demand of privacy and independence. In a closed …
[HTML][HTML] Benders decomposition for competitive influence maximization in (social) networks
Online social networks have become crucial to propagate information. Prominent use cases
include marketing campaigns for products or political candidates in which maximizing the …
include marketing campaigns for products or political candidates in which maximizing the …
Stochastic energy community trading model for day-ahead and intraday coordination when offering DER's reactive power as ancillary services
A two-stage stochastic programming energy trading model is presented in this article to
measure the distributed energy resources' capability to provide reactive power as ancillary …
measure the distributed energy resources' capability to provide reactive power as ancillary …
Data-driven two-stage distributionally robust optimization with risk aversion
R Huang, S Qu, Z Gong, M Goh, Y Ji - Applied Soft Computing, 2020 - Elsevier
This paper studies a two-stage distributionally robust optimization problem with risk
aversion. We define an ambiguity set containing the true distribution function with L 1 …
aversion. We define an ambiguity set containing the true distribution function with L 1 …
Large-scale influence maximization via maximal covering location
Influence maximization aims at identifying a limited set of key individuals in a (social)
network which spreads information based on some propagation model and maximizes the …
network which spreads information based on some propagation model and maximizes the …
Least-cost influence maximization on social networks
D Günneç, S Raghavan… - INFORMS Journal on …, 2020 - pubsonline.informs.org
Viral-marketing strategies are of significant interest in the online economy. Roughly, in these
problems, one seeks to identify which individuals to strategically target in a social network so …
problems, one seeks to identify which individuals to strategically target in a social network so …
An efficient linear programming based method for the influence maximization problem in social networks
E Güney - Information Sciences, 2019 - Elsevier
The influence maximization problem (IMP) aims to determine the most influential individuals
within a social network. In this study first we develop a binary integer program that …
within a social network. In this study first we develop a binary integer program that …
Influence maximization with deactivation in social networks
K Tanınmış, N Aras, IK Altınel - European Journal of Operational Research, 2019 - Elsevier
In this paper, we consider an extension of the well-known Influence Maximization Problem in
a social network which deals with finding a set of k nodes to initiate a diffusion process so …
a social network which deals with finding a set of k nodes to initiate a diffusion process so …