Experimental Work and Discussion of Results on Deepfakes in Stock Prices Using Sentiment Analysis and Machine Learning

Abstract

In the field of artificial intelligence, the employment of computer algorithms that develop themselves mechanically as they get more and more experience in experimental work and discussion of results on deepfakes is essential to the research process. It is frequently thought of as being in close proximity to artificial intelligence. Machine learning is a set of techniques that generates a model by making use of sample data, commonly referred to as training data, in order to make predictions about the future without actively attempting to do so, by separating the various types of tweets taken from the data on Twitter regarding a number of different companies. A classification algorithm was applied to the data that was collected and used in order to categorise the tweets. In addition, the OHLCV of the data from a number of different organisations is taken into account in order to improve efficiency.

Assessing the Influence of Investor Sentiment on the Performance of the Stock prices: Analyzing Stock Returns and Volatility During the COVID-19 Pandemic and Periods of Market Fluctuations.

“…These crashes show how much investor sentiment affects the value of assets. Several studies have also shown that there are good ways to trade based on changes in stock prices caused by how the market feels (Anbarasu, et al, 2023).…”