Critical impact of social networks infodemic on defeating coronavirus COVID-19 pandemic: Twitter-based study and research directions
News creation and consumption has been changing since the advent of social media. An
estimated 2.95 billion people in 2019 used social media worldwide. The widespread of the …
estimated 2.95 billion people in 2019 used social media worldwide. The widespread of the …
Co-authorship network analysis of AI applications in sustainable supply chains: Key players and themes
This research article presents a novel approach to examining the utilization of artificial
intelligence (AI) in sustainable supply chains (SSCs) by applying social network analysis …
intelligence (AI) in sustainable supply chains (SSCs) by applying social network analysis …
Influence decision models: From cooperative game theory to social network analysis
X Molinero, F Riquelme - Computer Science Review, 2021 - Elsevier
Cooperative game theory considers simple games and influence games as essential
classes of games. A simple game can be viewed as a model of voting systems in which a …
classes of games. A simple game can be viewed as a model of voting systems in which a …
Containment of rumor spread in complex social networks
L Yang, Z Li, A Giua - Information Sciences, 2020 - Elsevier
Rumors can propagate at great speed through social networks and produce significant
damages. In order to control rumor propagation, spreading correct information to …
damages. In order to control rumor propagation, spreading correct information to …
Link prediction in complex networks using node centrality and light gradient boosting machine
Link prediction is amongst the most crucial tasks in network science and graph data
analytics. Given the snapshot of a network at a particular instance of time, the study of link …
analytics. Given the snapshot of a network at a particular instance of time, the study of link …
Ranking influential spreaders based on both node k-shell and structural hole
The ranking of individual spreaders aims to measure the influential capability of individual
nodes and is important to control information spreading in a network. However, many …
nodes and is important to control information spreading in a network. However, many …
Influence maximization in complex networks by using evolutionary deep reinforcement learning
Influence maximization (IM) in complex networks tries to activate a small subset of seed
nodes that could maximize the propagation of influence. The studies on IM have attracted …
nodes that could maximize the propagation of influence. The studies on IM have attracted …
Vital spreaders identification in complex networks with multi-local dimension
The important nodes identification has been an interesting problem in this issue. Several
centrality methods have been proposed to solve this problem, but most previous methods …
centrality methods have been proposed to solve this problem, but most previous methods …
A multi-objective linear threshold influence spread model solved by swarm intelligence-based methods
The influence maximization problem (IMP) is one of the most important topics in social
network analysis. It consists of finding the smallest seed of users that maximizes the …
network analysis. It consists of finding the smallest seed of users that maximizes the …
Trade structure and risk transmission in the international automotive Li-ion batteries trade
Lithium-ion batteries (LIBs) are an essential part for electric vehicles (EVs) and have
experienced rapid growth with the strong demand for EVs. Concerns over the sustainable …
experienced rapid growth with the strong demand for EVs. Concerns over the sustainable …