: 107-116
Received: March 12, 2024
Revised: March 28, 2024
Accepted: April 01, 2024
Lviv Polytechnic National University
Lviv Polytechnic National University
Lviv Polytechnic National University

Today, an important problem of financial successis to find effective trading approaches that can adapt to rapidly changing market conditions and ensure high investment returns. Based on the literature analysis, ChatGPT is identified as a promising technology that is more effective than FinBert in being used as a component for conducting sentiment analysis of stocks. The research also shows satisfactory efficiency and productivity of ChatGPT. Existing sources do not provide a detailed description of the automation of the sentiment analysis process and testing of the ChatGPT model on big data. The purpose of the performed research is to develop an automated system for sentiment analysis based on ChatGPT with an integrated news aggregator for collecting and analyzing financial data.The study details the creation of a comprehensive solution sketch. A plan is presented that covers the entire range of the proposed system. A preliminary application architecture has been developed that provides a visual and structural representation of how the various components of the solution interact and function in a coordinated manner. This architectural plan serves as a roadmap for the implementation and deployment of the automated sentiment analyzer, ensuring clarity and accuracy in its design. Initial diagrams of the relationships between the entities in the system have been developed and an algorithm for the system has been proposed. Further research will focus on creating a minimum working system for the sentiment analyzer and evaluating its efficiency and quality of work.

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[6] Telegram API [Електронний ресурс] – режим доступу:

[7] Telethon’sDocumentation [Електронний ресурс] – режим доступу: