Curated-Monitored Language and the Restriction of Meaning in the Digital Sphere: A Descriptive-Analytical Study of Pragmatic Constraint and the Formation of Linguistic Bubbles within the Smart Media Economy - the Blockout 2024 Campaign as a Model

Abstract

This study analyzes the Blockout 2024 campaign as a significant case of how political expression is shaped within AI-driven digital environments. It explores the construction and restriction of meaning through curated language strategies like repetition, reduction, and omission, particularly across platforms, such as Twitter, Instagram, and TikTok. The research examines the symbolic and rhetorical tools—including images, slogans, and hashtags— that encode protest discourse. It highlights algorithmic censorship mechanisms, such as content deletion and restricted visibility that reshape meaning as well as limit interpretive reach. The study also investigates how algorithmic logic reinforces discursive closure and reduces dialogic diversity. Methodologically, it adopts an interdisciplinary approach combining digital sociology, semiotics, and discourse analysis, supported by precise statistical tools. The latter provides in-depth insights into protest discourse under algorithmic governance.