The central community of twitter ego-networks as a means for fake influencer detection
Authors: Ntalianis, Klimis 
Anastasopoulou, Vasiliki 
Tsapatsoulis, Nicolas 
Publisher: IEEE
Issue Date: 1-Aug-2019
Conference: 2019 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech), 5-8 August 2019, Fukuoka, Japan 
Book: Proceedings on the IEEE 17th International Conference on Dependable, Autonomic and Secure Computing, IEEE 17th International Conference on Pervasive Intelligence and Computing, IEEE 5th International Conference on Cloud and Big Data Computing, 4th Cyber Science and Technology Congress, (DASC-PiCom-CBDCom-CyberSciTech 2019) 
Keywords: Community detection, Degeneracy, Genetic algorithms, Graph partitioning, K-core, Social networks, Twitter ego networks
Abstract: 
The central community of social networks, usually represented through the highest degree k-core of the corresponding graph, is proposed here as a compact representation of large social networks. We show that the central community of egocentric social media networks, such as the ego networks on Twitter and Instagram, tell us much more about the actual influence of the ego than the whole egocentric ...
ISBN: 978-1-7281-3024-8
DOI: 10.1109/DASC/PiCom/CBDCom/CyberSciTech.2019.00042
URI: https://uniwacris.uniwa.gr/handle/3000/2921
Type: Conference Paper
Department: Department of Business Administration 
School: School of Administrative, Economics and Social Sciences 
Affiliation: University of West Attica (UNIWA) 
Appears in Collections:Book Chapter / Κεφάλαιο Βιβλίου

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