Examining Intensive Groups in YouTube Commenter Networks

Focal structures are the sets of individuals in social networks that are not influential on their own but are influential collectively. These individuals, when coordinating, can be responsible for massive information diffusion, influence operations, or could coordinate (cyber)-attacks. These communities have high tension than other communities in the social network and can mobilize crowds. In this research, we propose a two-level decomposition optimization method for identifying these intensive groups in the complex social networks by constructing a two-level optimization problem for maximizing the local individual’s degree centrality values and the global modularity measures. We also demonstrate the assembled centrality modularity method by applying to a network of YouTube users commenting on conspiracy theory videos to identify coordinating commenters. The dataset consisted of 9,661 users commenting on 4,145 conspiracy theory videos and the derived commenter network contained more than 4.4 million edges. Focal structure analysis was applied to this network to identify sets of users that are coordinating to promote disinformation dissemination. Our proposed model identifies smallest atomic units having high influence, interactions, higher reachability for information propagation. A multi-criteria optimization problem is also employed to rank the identified sets for further investigations.