Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/18981
Title: The Central Community of Twitter ego-Networks as a Means for Fake Influencer Detection
Authors: Tsapatsoulis, Nicolas 
Anastasopoulou, Vasiliki 
Ntalianis, Klimis S. 
Major Field of Science: Natural Sciences
Field Category: Computer and Information Sciences
Keywords: Community detection;Degeneracy;Genetic algorithms;Graph partitioning;K-core;Social networks;Twitter ego networks
Issue Date: 4-Nov-2019
Source: IEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing, Cyber Science and Technology Congress, 2019, 5-8 August, Fukuoka, Japan
Project: EnhaNcing seCurity And privacy in the Social wEb: a user centered approach for the protection of minors 
Conference: IEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing, Cyber Science and Technology Congress 
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 network itself. We also propose a novel genetic algorithm for the identification of central community of egocentric social networks and we examine the importance of the proper initialisation of this algorithm. The actual Twitter ego networks we used in our experiments along with the corresponding Python code are made publicly available for anyone who wishes to use them.
URI: https://ktisis.cut.ac.cy/handle/10488/18981
ISBN: 978-1-7281-3024-8
DOI: 10.1109/DASC/PiCom/CBDCom/CyberSciTech.2019.00042
Rights: © IEEE
Type: Conference Papers
Affiliation : Cyprus University of Technology 
National and Kapodistrian University of Athens 
University of West Attica 
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers - poster -presentation

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