Sockpuppet Detection: a Telegram case study
This addresses the issue of online abuse and misinformation for users and moderators on Telegram, but appears incremental as it applies known sockpuppet detection concepts to a new platform.
The study tackled the problem of detecting sockpuppet accounts on Telegram, which are fake identities used for abusive behaviors like opinion manipulation and spreading fake news, by focusing on this specific platform known for high levels of offensive activities.
In Online Social Networks (OSN) numerous are the cases in which users create multiple accounts that publicly seem to belong to different people but are actually fake identities of the same person. These fictitious characters can be exploited to carry out abusive behaviors such as manipulating opinions, spreading fake news and disturbing other users. In literature this problem is known as the Sockpuppet problem. In our work we focus on Telegram, a wide-spread instant messaging application, often known for its exploitation by members of organized crime and terrorism, and more in general for its high presence of people who have offensive behaviors.