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Opinion leaders' detection in dynamic social networks
Author(s) -
Oueslati Wided,
Arrami SeifAllah,
Dhouioui Zeineb,
Massaabi Marwa
Publication year - 2020
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5692
Subject(s) - public opinion , opinion leadership , task (project management) , computer science , data science , social media , context (archaeology) , social network (sociolinguistics) , sentiment analysis , public relations , political science , artificial intelligence , politics , world wide web , engineering , paleontology , systems engineering , law , biology
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.