Volume 12 (2024)
Volume 11 (2023)
Volume 10 (2022)
Volume 9 (2021)
Volume 8 (2020)
Volume 7 (2019)
Volume 6 (2018)
Volume 5 (2017)
Volume 4 (2016)
Volume 3 (2015)
Volume 2 (2014)
Volume 1 (2013)
H.3. Artificial Intelligence
Identification of Influential Nodes in Social Networks based on Profile Analysis

Zeinab Poshtiban; Elham Ghanbari; Mohammadreza Jahangir

Volume 11, Issue 4 , November 2023, , Pages 535-545


  Analyzing the influence of people and nodes in social networks has attracted a lot of attention. Social networks gain meaning, despite the groups, associations, and people interested in a specific issue or topic, and people demonstrate their theoretical and practical tendencies in such places. Influential ...  Read More

H.3. Artificial Intelligence
Link Prediction in Social Networks: A Bibliometric Analysis and Review of Literature (1987-2021)

Akram Pasandideh; Mohsen Jahanshahi

Volume 11, Issue 3 , July 2023, , Pages 487-504


  Link prediction (LP) has become a hot topic in the data mining, machine learning, and deep learning community. This study aims to implement bibliometric analysis to find the current status of the LP studies and investigate it from different perspectives. The present study provides a Scopus-based bibliometric ...  Read More

GroupRank: Ranking Online Social Groups Based on User Membership Records

A. Hashemi; M. A. Zare Chahooki

Volume 9, Issue 1 , January 2021, , Pages 45-57


  Social networks are valuable sources for marketers. Marketers can publish campaigns to reach target audiences according to their interest. Although Telegram was primarily designed as an instant messenger, it is used as a social network in Iran due to censorship of Facebook, Twitter, etc. Telegram neither ...  Read More

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

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

Volume 8, Issue 4 , November 2020, , Pages 545-555


  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
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 , April 2020, , Pages 201-212


  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
Using an Evaluator Fixed Structure Learning Automata in Sampling of Social Networks

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

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


  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