This paper aims to develop a sentiment analysis tool to detect the rise of potential meme stocks in a timely manner.

For this purpose, a literature review was conducted to identify two large language models (LLMs), OpenAI and Hugging Face, which can be accessed via an application programming interface (API). The literature review also highlighted the importance of early detection of meme stocks.

It is suggested that the LLMs should first be used to scrape news feeds for companies facing financial difficulties. Additionally, factors such as their business model or product benefiting from the coronavirus disease 2019 (COVID-19) pandemic should be considered. The short sales ratio and the criteria of an iconic brand were also examined. Consequently, an analysis of time series data of the potential stock was conducted in parallel with sentiment analysis of social media networks. This study offers practical insights and a tailored meme stock business tool for retail investors and the financial market.