How the Bank of Russia Is Perceived on Telegram Channels: Building an Index Using Machine Learning Methods

Alisa Polekhina () and Anna Guseva ()
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Alisa Polekhina: Bank of Russia
Anna Guseva: Bank of Russia

Russian Journal of Money and Finance, 2025, vol. 84, issue 3, 28-62

Abstract: The paper constructs a Bank of Russia perception index on Telegram channels, which may serve as a leading indicator of public confidence in the regulator (correlation with InFOM survey data – 74%). The index is estimated on unstructured data from 1,400 Telegram channels. This is the first index of its kind, providing a comprehensive picture of the information field by classifying channels into types and key areas of the Bank of Russia's activities, from monetary policy to the financial market and the national payment system. For text analysis, we use both the traditional dictionary method and modern large linguistic models. The final index correlates with household inflation expectations and business price expectations but has no statistical link to financial market variables. The index opens up new opportunities for researching public perception of the Bank of Russia's policy and can be used as a tool for assessing the effectiveness of its communication.

Keywords: sentiment index; machine learning; natural language processing; semantic analysis; inflation expectations; Telegram (search for similar items in EconPapers)
JEL-codes: C55 C63 D83 E52 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:bkr:journl:v:84:y:2025:i:3:p:28-62

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