SPECIAL ISSUE PAPER
Opinion leaders' detection in dynamic social networks
Wided Oueslati,
SeifAllah Arrami,
Zeineb Dhouioui,
Marwa Massaabi,
Wided Oueslati
BESTMOD, Institut Supérieur de Gestion, University of Tunis, Tunis, Tunisia
Search for more papers by this authorSeifAllah Arrami
Ecole Supérieure de Commerce de Tunis, University of Manouba, Manouba, Tunisia
Search for more papers by this authorZeineb Dhouioui
BESTMOD, Institut Supérieur de Gestion, University of Tunis, Tunis, Tunisia
Search for more papers by this authorCorresponding Author
Marwa Massaabi
BESTMOD, Institut Supérieur de Gestion, University of Tunis, Tunis, Tunisia
Correspondence Marwa Massaabi, BESTMOD, Institut Supérieur de Gestion, University of Tunis, Tunis, Tunisia.
Email: [email protected]
Search for more papers by this authorWided Oueslati,
SeifAllah Arrami,
Zeineb Dhouioui,
Marwa Massaabi,
Wided Oueslati
BESTMOD, Institut Supérieur de Gestion, University of Tunis, Tunis, Tunisia
Search for more papers by this authorSeifAllah Arrami
Ecole Supérieure de Commerce de Tunis, University of Manouba, Manouba, Tunisia
Search for more papers by this authorZeineb Dhouioui
BESTMOD, Institut Supérieur de Gestion, University of Tunis, Tunis, Tunisia
Search for more papers by this authorCorresponding Author
Marwa Massaabi
BESTMOD, Institut Supérieur de Gestion, University of Tunis, Tunis, Tunisia
Correspondence Marwa Massaabi, BESTMOD, Institut Supérieur de Gestion, University of Tunis, Tunis, Tunisia.
Email: [email protected]
Search for more papers by this authorSummary
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.
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