An Application of Advanced Sentiment Analysis on X (Twitter) Utilising Large Language Models for the Precise Prediction of Election Outcomes

In this research project, we harness the capability of Large Language Models especially GPT to perform sentiment analysis on Twitter, aiming to forecast election results.The widespread adoption of digital technologies has precipitated a notable escalation in the creation of user-generated content, thereby catalysing a transformative shift in communication dynamics across multiple platforms.Social media platforms, in particular, have emerged as reservoirs of invaluable behavioural data, offering profound insights across a spectrum of disciplines including politics, e-commerce, education and medical.Engaging in political tweet mining for predictive analytics presents formidable hurdles, notably encompassing the precise determination of sentiment accuracy and the identification of propagandistic narratives.We propose LLMs, particularly GPT, as a solution due to their adeptness in natural language processing (NLP) tasks.LLMs' extensive training enables them to understand intricate linguistic nuances, including sentiment and context.Their generative capabilities ensure coherent text production, crucial for sentiment analysis.Leveraging these advantages, we aim to predict outcomes for the Indian Lok Sabha Elections 2024 through sentiment analysis using GPT models.This research addresses the pressing need for robust methodologies in predicting election results by tapping into the power of LLMs and NLP techniques.