Link prediction finds missing links (in static networks) or predicts the likelihood of future links
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …

The growing popularity of social networks is providing a promising opportunity for different
practical applications. The influence analysis is an essential technique supporting the …

The influence maximization (IM) problem identifies the subset of influential users in the
network to provide solutions for real-world problems like outbreak detection, viral marketing …

The different communications of users in social networks play a key role in effect to each
other. The effect is important when they can achieve their goals through different …

Online social networks play an essential role in propagating information, innovation, and
ideas via word-of-mouth spreading. This word-of-mouth phenomenon leads to a …

Targeted immunization is a commonly used strategy in preventing epidemic spreading.
Traditional methods immunize targeted nodes based on specific global or local network …

Due to the explosive rise of online social networks, social network analysis (SNA) has
emerged as a significant academic field in recent years. Understanding and examining …

Community detection in social networks is an important field of research in data mining and
has an abundant literature. Time varying social networks require algorithms that can comply …

In recent years, most link prediction algorithms have focused on node similarity owing to the
associated low computational complexity and promising accuracy. In addition to the …

The main goal in the influence maximization problem (IMP) is to find k minimum nodes with
the highest influence spread on the social networks. Since IMP is NP-hard and is not …