TY - GEN
T1 - Collapse of Online Social Networks
T2 - 2020 IEEE Globecom Workshops, GC Wkshps 2020
AU - Rehman, Ateeq Ur
AU - Tariq, Rizwan
AU - Rehman, Abdul
AU - Paul, Anand
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12
Y1 - 2020/12
N2 - There is a rapid increase in online social networks (OSN) due to the development of information and communication technologies (ICT). People around the globe are adopting the new OSN to keep in touch with friends and family members, to remain updated with the latest trends and news, etc. In almost every OSN, few influential users are active and attract other members and make clusters. Many users connect with these influential users to remain in touch with the latest ongoing trends as the influential nodes come up with the latest news. In this work, the structural analysis of the Facebook network is undergone. The influential nodes have been identified based on betweenness centrality (BC) and degree centrality (DC) measures. Further, community detection has been made in the whole network especially around the influential nodes. Upon filtration of four top-ranked nodes selected based on the high value of BC and DC, only 22.75% nodes and 8.87% remain in the network. Hence, there is a big question about the sustainability of OSN.
AB - There is a rapid increase in online social networks (OSN) due to the development of information and communication technologies (ICT). People around the globe are adopting the new OSN to keep in touch with friends and family members, to remain updated with the latest trends and news, etc. In almost every OSN, few influential users are active and attract other members and make clusters. Many users connect with these influential users to remain in touch with the latest ongoing trends as the influential nodes come up with the latest news. In this work, the structural analysis of the Facebook network is undergone. The influential nodes have been identified based on betweenness centrality (BC) and degree centrality (DC) measures. Further, community detection has been made in the whole network especially around the influential nodes. Upon filtration of four top-ranked nodes selected based on the high value of BC and DC, only 22.75% nodes and 8.87% remain in the network. Hence, there is a big question about the sustainability of OSN.
KW - Betweenness Centrality
KW - Community Detection
KW - Degree Centrality
KW - Online social network
KW - Social Internet of Things
UR - http://www.scopus.com/inward/record.url?scp=85102951991&partnerID=8YFLogxK
U2 - 10.1109/GCWkshps50303.2020.9367407
DO - 10.1109/GCWkshps50303.2020.9367407
M3 - Conference contribution
AN - SCOPUS:85102951991
T3 - 2020 IEEE Globecom Workshops, GC Wkshps 2020 - Proceedings
BT - 2020 IEEE Globecom Workshops, GC Wkshps 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 7 December 2020 through 11 December 2020
ER -