Amazon Research Award Proposal: Using Agent-Based Modeling for Bot Detection in Online Social Networks
Overview:
Online Social Networks (OSN) are emerging in this new era. The number of Social Network users have been increasing tremendously within the last decade. People can no longer avoid the ubiquitous presence of OSNs. Many social and political topics are widely discussed across these platforms and these discussions have been shown to have the potential to influence the masses and potentially affect how they react to it. This shows how popular these OSNs are but at the same time users have to face a lot of problems like bots, abuse, security and privacy problems, identity thefts, fake profiles, spammers, malwares, rumors and cyber threats among other things. The research is focused on bot detection in online social networks, which can minimize a user’s risk to malicious rumors and the spread of false or misleading information amongst many other issues. There are number of existing techniques for online social network bot detection. Most of the existing approaches are able to detect the bots accurately but they cannot completely protect against them.
Principal Investigators:
Dr. Ivan Garibay
Sponsors:
