title: Quantification and interpretation of socio-economic environment and its effects on the cryptocurrency market using machine learning methods
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: ÐÐ¾Ð»Ð¸ÑÐµÑÑÐ²ÐµÐ½Ð½Ð°Ñ Ð¾ÑÐµÐ½ÐºÐ° Ð¸ Ð¸Ð½ÑÐµÑÐ¿ÑÐµÑÐ°ÑÐ¸Ñ ÑÐ¾ÑÐ¸Ð°Ð»ÑÐ½Ð¾-ÑÐºÐ¾Ð½Ð¾Ð¼Ð¸ÑÐµÑÐºÐ¾Ð¹ ÑÑÐµÐ´Ñ Ð¸ ÐµÐµ Ð²Ð»Ð¸ÑÐ½Ð¸Ñ Ð½Ð° ÐºÑÐ¸Ð¿ÑÐ¾Ð²Ð°Ð»ÑÑÐ½ÑÐ¹ ÑÑÐ½Ð¾Ðº Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ
Creators: name: Ð¨Ð°Ð´ÑÐ¾Ð², ÐÐ¸ÑÐ¸Ð»Ð»
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: cryptocurrencies
information environment
investments
machine learning
media sites
emotinal coloring

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description: This Masterâs dissertation is focusing on the connection between the emotions conveyed in the news postings on Cryptocurrency-adjacent Telegram channels and the changes in the market dynamics. The paper starts with an extensive theoretical basis on how social media postings across various platforms have been speculated to influence the prices of cryptocurrencies and other products. Over the course of the research, a large quantity of data was gathered and processed with Natural Language Processing tools to create a dataset filled with quantitative markers of various emotions, which in turn, coupled with the prices of Bitcoin over the period between 2020 and 2023 was fed to machine learning algorithm to provide predictive results. Several models such as Linear Regression, Decision Tree, Random Forest and Gradient Boosting have been used in research. Gradient boosting model provided coefficient of determination close to 0,72 with minimal errors and was deemed most effective in matters of predicting the Bitcoin price point changes with minimal outliers. The final model proves the connection between the social media posts on Telegram and returns on Bitcoin and the effect social media has on the market. That opens a field of future research in the fields of economics, finance and even computer science. The practical result of the research is a predictive model which can be used both alongside traditional predictive methods and by itself, providing professional and amateur investors with a powerful tool which allows them to take another factor into account when making financial decisions.