This paper extensively reviews the literature of community detection in complex networks
and proposes a general classification describing the main models used for this purpose …

Influence maximization is the process of identifying a small set of influential nodes from a
complex network to maximize the number of activation nodes. Due to the critical issues such …

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 …

Community detection in large-scale networks is one of the main challenges in social
networks analysis. Proposing a fast and accurate algorithm with low time complexity is vital …

In this paper, we explore influence maximization, one of the most widely studied problems in
social network analysis. However, develo** an effective algorithm for influence …

Influence maximization problem aims to find a set of nodes with the highest diffusion in
social networks in order to maximize diffusion in the graph by this set. A set of these nodes …

The influence maximization problem has gained particular importance in viral marketing for
large-scale spreading in social networks. Develo** a fast and appropriate algorithm to …

Large-scale group decision-making (LSGDM) serves as a pivotal tool for facilitating
consistent decision results through intricate interactions among individuals within the …

Parallel and distributed community detection in large-scale complex networks, such as
social networks, is a challenging task. Parallel and distributed algorithm with high accuracy …

Social network analysis (SNA) has opened up different research areas to researchers, such
as Community Detection and Influence Maximization. By modeling social networks as …