Volume 14, Issue 1 (3-2022)                   itrc 2022, 14(1): 38-47 | Back to browse issues page

XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Vafaei N, Keyvanpour M R. A Community-Based Method for Identifying Influential Nodes Using Network Embedding. itrc. 2022; 14 (1) :38-47
URL: http://ijict.itrc.ac.ir/article-1-528-en.html
1- Department of Computer Engineering Faculty of Engineering Alzahra University Tehran, Iran
2- Department of Computer Engineering Faculty of Engineering Alzahra University Tehran, Iran , keyvanpour@alzahra.ac.ir
Abstract:   (103 Views)
 People's influence on their friends' personal opinions and decisions is an essential feature of social networks. Due to this, many businesses use social media to convince a small number of users in order to increase awareness and ultimately maximize sales to the maximum number of users. This issue is typically expressed as the influence maximization problem. This paper will identify the most influential nodes in the social network during two phases. In the first phase, we offer a community detection approach based on the Node2Vec method to detect the potential communities. In the second phase, larger communities are chosen as candidate communities, and then the heuristicbased measurement approach is utilized to identify influential nodes within candidate communities. Evaluations of the proposed method on three real datasets demonstrate the superiority of this method over other compared methods.
Full-Text [PDF 1171 kb]   (44 Downloads)    
Type of Study: Research | Subject: Information Technology

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.