The 4th Stage of Genocide: Computational Analysis of Dehumanization of Ukrainians on Russian Telegram

Abstract

Dehumanization is a pernicious psychological process of denying some or all attributes of humanness to the target group. It is frequently cited as a common hallmark of incitement to commit genocide. The international security landscape has seen a dramatic shift following the 2022 Russian invasion of Ukraine. This, coupled with recent developments in the conceptualization of dehumanization, necessitates the creation of new techniques. These techniques need to be capable of analyzing and detecting this extreme violence-related phenomenon on a large scale. Our project aims to pioneer the development of a detection system for instances of dehumanization in the Russian language. To achieve this, we collected the entire posting history of the most popular political bloggers on Russian Telegram. We tested classical machine learning, deep leaning, and zero-shot learning approaches and applied semantic modeling to explore the evolution of dehumanizing rhetoric. We found that transformer-based method for entity extraction shows promising results for binary dehumanization classification when applied via an indicator mapping function, while additionally allowing for evaluation of the type of dehumanization instance. The proposed methods can be built into systems of anticipatory governance, contribute to the collection of evidence of genocidal intent in the Russian invasion of Ukraine, and pave the way to the large-scale studies of dehumanizing language and representation of Ukrainians in Russian media.