Opinion mining plays a critical role in understanding public sentiment and preferences,
particularly in the context of political elections. Traditional polling methods, while useful, can
be expensive and less scalable. Social media offers an alternative source of data for opinion
mining but presents challenges such as noise, biases, and platform limitations in data
collection. In this paper, we propose a novel approach for opinion mining, utilizing
YouTube's auto-generated captions from public interviews as a data source, specifically …