This study focuses on political sentiment analysis during Bangladeshi elections, using the "Motamot" dataset to evaluate how Pre-trained Language Models (PLMs) and Large Language Models (LLMs) capture complex sentiment characteristics. The research explores the effectiveness of various models and learning strategies in understanding public opinion.