Identifying influential nodes in a network is vital for the study of social network structure and
to facilitate the dissemination of requisite information. The challenge we address is that …

Various opportunities are available to depict different domains due to the diverse nature of
social networks and researchers' insatiable. An opinion leader is a human entity or cluster of …

The influence of each entity in a network is a crucial index of the network information
dissemination. Greedy influence maximization algorithms suffer from time efficiency and …

Influence maximization (IM) is a challenge in social networks, which depends on the
spreader selection. We propose a quadratic programming model to identify a fixed number …

Influence maximization (IM), as an essential problem in social network analysis, can identify
a minimum group of the influential nodes to maximize the spread of information on the …

Computing influential nodes gets a lot of attention from many researchers for information
spreading in complex networks. It has vast applications, such as viral marketing, social …

Group polarization effect reveals a phenomenon that discussions could lead to an increase
in the extremism among members in a group. For the first time, the information propagation …

Trust relationship prediction has gained a lot of interest in online social networks as it allows
users to escape complex analysis in decision-making. However, most existing work fail to …

The booming development of online social media has changed the way people post and
access information. The authenticity of content is weakened, and all kinds of misinformation …

Viral marketing relies on a set of users who have characteristics to rapidly increase the
propagation of information. In viral marketing, information reaches and is shared by the …