Online abusive users analytics through visualization

Anna Cinzia Squicciarini, Jules Dupont, Ruyan Chen

Abstract: In this demo, we present Abuse User Analytics (AuA), an analytical framework aiming to provide key information about the behavior of online social network users. AuA efficiently processes data from users' discussions, and renders information about users' activities in a easy to-understand graphical fashion with the goal of identifying deviant or abusive activities. Using animated graphics, AuA visualizes users' degree of abusiveness, measured by several key metrics, over user selected time intervals. It is therefore possible to visualize how users' activities lead to complex interaction networks, and highlight the degenerative connections among users and within certain threads.