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In informational autocracies, controlling narratives and shaping public opinion are primarily achieved through propaganda and censorship. While the overt actions of the state are evident, the subtle dynamics of self-censorship in online platforms remain largely underexplored. Our study turns to Telegram in Russia, providing an invaluable context to delve into the intricacies of self-censorship. Historically, comprehensive studies on online censorship within Telegram have been scant, attributed to the complexities of data collection and the limited analytical tools available. Utilizing an extensive 8-terabyte dataset, which encompasses posts from a majority of Telegram channels in the Russian domain, we systematically identify instances of post deletions. These deletions serve as clear markers of self-censorship. Our analysis further extends to various channel-level factors, such as ideological orientation, audience size, competition for audience attention, and network surroundings, assessing their influence on the magnitude of self-censorship in a channel. Through this rigorous examination, our research unveils the mechanisms by which informational autocracies might indirectly exert pressure, compelling individuals or entities to self-censor. Our findings significantly contribute to a comprehensive understanding of the nuanced methods through which informational autocracies operate in digital spaces, particularly in driving self-censorship behaviors.