Opinion leaders' detection in dynamic social networks. (14th April 2020)

• Record Type: Journal Article
• Authors: Oueslati, Wided; Arrami, SeifAllah; Dhouioui, Zeineb; Massaabi, Marwa
• Other Names: Schifanella Claudio guestEditor.; Bracciali Andrea guestEditor.; Benkrid Soumia guestEditor.; Moussa Rim guestEditor.; Badir Hassan guestEditor.; Lo Moussa guestEditor.; Bellatreche Ladjel guestEditor.
• Is Part Of: Concurrency and computation. Volume 33:Number 1(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-04-14
• Subjects: dynamic detection -- Facebook -- opinion leader -- opinion term frequency -- social signals; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.5692
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: Social media networks have revolutionized the way users interact and express their opinion. Obviously, identifying opinion leaders has a widespread applicability. For instance, by detecting leaders, companies can manipulate the public opinion. However, this task is challenging due to the complexity and the ceaseless change of the social networks structure. Yet, existing opinion leaders 'detection methods have essentially focused on static social graphs neglecting the temporal characteristics. Therefore, the necessity of identifying opinion leaders seems to be more and more crucial. In this context, we present a new approach for detecting opinion leaders based on analyzing online community interactions and dealing with the dynamic aspect of social networks. The experiments are performed on real data and the comparison of the proposed approach with commonly used approaches showed a good performance.