Computational Data and Social Networks

Beschreibung

This book constitutes the refereed proceedings of the 10th International Conference on Computational Data and Social Networks, CSoNet 2021, which was held online during November 15-17, 2021. The conference was initially planned to take place in Montreal, Quebec, Canada, but changed to an online event due to the COVID-19 pandemic. 

The 24 full and 8 short papers included in this book were carefully reviewed and selected from 57 submissions. They were organized in topical sections as follows: Combinatorial optimization and learning; deep learning and applications to complex and social systems; measurements of insight from data; complex networks analytics; special track on fact-checking, fake news and malware detection in online social networks; and special track on information spread in social and data networks.

Autor*in

David Mohaisen

Themen in »Computational Data and Social Networks«

adversarial attacks of network artificial intelligence computational methods for social good computer networks data mining graph theory influence modeling machine learning maximization network organization network protocols NLP and affective computing propagation security, trust and privacy semantics

Stimmen zu »Computational Data and Social Networks«

Details

Link teilen