Sockpuppet Detection: a Telegram case study

TL;DR

This paper investigates sockpuppet detection in Telegram, addressing the challenge of identifying multiple fake accounts created by the same individual to manipulate, spread misinformation, or conduct malicious activities.

Contribution

It provides a case study on Telegram, highlighting detection methods for sockpuppets in a platform known for organized crime and offensive behaviors.

Findings

Identifies characteristics of sockpuppets in Telegram

Proposes detection techniques tailored to Telegram's environment

Highlights the prevalence of sockpuppets in malicious activities

Abstract

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.