  The study of how social media affects the formation of public opinion and its
influence on political results has been a popular field of inquiry. However,
current approaches frequently offer a limited comprehension of the complex
political phenomena, yielding inconsistent outcomes. In this work, we introduce
a new method: harnessing the capabilities of Large Language Models (LLMs) to
examine social media data and forecast election outcomes. Our research diverges
from traditional methodologies in two crucial respects. First, we utilize the
sophisticated capabilities of foundational LLMs, which can comprehend the
complex linguistic subtleties and contextual details present in social media
data. Second, we focus on data from X (Twitter) in India to predict state
assembly election outcomes. Our method entails sentiment analysis of
election-related tweets through LLMs to forecast the actual election results,
and we demonstrate the superiority of our LLM-based method against more
traditional exit and opinion polls. Overall, our research offers valuable
insights into the unique dynamics of Indian politics and the remarkable impact
of social media in molding public attitudes within this context.
