1. DINGA: A Genetic-algorithm-based Method for Finding Important Nodes in Social Networks

H. Rahmani; H. Kamali; H. Shah-Hosseini

Articles in Press, Accepted Manuscript, Available Online from 23 June 2020

Abstract
  Nowadays, a significant amount of studies are devoted to discovering important nodes in graph data. Social networks as graph data have attracted a lot of attention. There are various purposes for discovering the important nodes in social networks such as finding the leaders in them, i.e. the users who ...  Read More

D. Data
2. Community Detection using a New Node Scoring and Synchronous Label Updating of Boundary Nodes in Social Networks

M. Zarezade; E. Nourani; Asgarali Bouyer

Volume 8, Issue 2 , Spring 2020, , Pages 201-212

Abstract
  Community structure is vital to discover the important structures and potential property of complex networks. In recent years, the increasing quality of local community detection approaches has become a hot spot in the study of complex network due to the advantages of linear time complexity and applicable ...  Read More

H.3. Artificial Intelligence
3. Using an Evaluator Fixed Structure Learning Automata in Sampling of Social Networks

S. Roohollahi; A. Khatibi Bardsiri; F. Keynia

Volume 8, Issue 1 , Winter 2020, , Pages 127-148

Abstract
  Social networks are streaming, diverse and include a wide range of edges so that continuously evolves over time and formed by the activities among users (such as tweets, emails, etc.), where each activity among its users, adds an edge to the network graph. Despite their popularities, the dynamicity and ...  Read More