Prof. Dr. Nitin Agarwal,
University of Arkansas at Little Rock, USA
Networks and Narratives Characterizing Multiplatform Influence Campaigns to Strengthen Socio-cognitive Security
With the proliferation of smart devices, mobile applications, and social network platforms, the social side effects of these technologies have become more profound, especially in social and political disintegration. Several journalistic and academic investigations have reported that modern communication platforms such as social media are strategically used to coordinate cyber influence campaigns. Several researchers have studied these campaigns and identified various tactics, techniques, and procedures used by various online deviant groups, e.g., online propagandists groups or extremist/terrorist group sympathizers. Various social media platforms utilize research findings to detect and regulate some of these campaigns, however, the techniques that are used evolve and adapt to go undetected. This is a growing problem. This session aims to have a scientific discussion among experts who study deviant activities on social media, including but not limited to, detection of deviant/disruptive behaviors on social media; misinformation detection, identification, and dissemination; case studies of misinformation; etc.
This includes the following topics:
– Misinformation, disinformation, rumor, propaganda, influence campaign detection;
– Tactics and strategies used to conduct misinformation;
disinformation, rumor, propaganda, influence campaigns;
– Deviant behaviors on social media platforms (cyber threats, cybercrime, cyber bullying, trolling, spamming, etc.);
– Coordination campaigns;
– Cyber Flash Mobs;
– Algorithmic manipulation such as exploiting recommendation bias;
– Detection/modeling of inorganic behaviors (bots, botnets, social bots, etc.) and their evolution dynamics;
– Hate Speech (toxic, polarizing, or disruptive content);
– Computational extraction of narratives used in misinformation, disinformation, rumor, propaganda, influence campaigns.