DIGITAL ASTROTURFING IN TELEGRAM: SOCIOLINGUISTIC MECHANISMS AND LINGUISTIC MARKERS OF INFLUENCE

Abstract

This article presents a comprehensive sociolinguistic analysis of digital astroturfing mechanisms within the Ukrainian segment of Telegram, utilizing the community “Povernit cholovika!!!” (“Bring My Husband Back!!!”) as a primary case study. By examining the operational specifics of pseudo-grassroots online groups, the study investigates contemporary manipulative technologies, focusing on strategies of artificial social polarization and the construction of conflict-driven group identities.
The research introduces the concept of “digital astroturfing” into Ukrainian sociolinguistic discourse as a tool of information-psychological influence and proposes an original definition for the term “pseudo-grassroots network community.” The paper explores the role of language in shaping the “us–them” dichotomy, analyzing the discourse of the target Telegram channel as an environment where hostile narratives are disguised as civic engagement.
Particular attention is paid to identifying and classifying lexical markers that signal the artificial nature of the communication. The analysis reveals multiple levels of linguistic interference – graphic-orthographic, morphological, and lexical. Notably, the study documents the systematic use of Latin homoglyphs and Russian calques, which undermine the speaker’s purported authenticity. Furthermore, the article analyzes the use of hate speech and specific syntactic devices designed to induce suggestibility and suppress critical thinking.
The study traces the evolution of the community’s communicative strategy, highlighting a shift in linguistic behavior from expressives (simulating despair) to directives (inciting violence). It also identifies social engineering mechanisms aimed at dehumanizing state representatives and legitimizing aggression. The findings demonstrate that the examined resource functions as an instrument of hostile influence intended to destabilize Ukrainian society.
These results offer practical applications for monitoring the information space, developing algorithms to identify pseudo-grassroots communities, and countering hostile propaganda.