Analysis of Sentiment in YouTube Comments for 2024 Political Campaigns for Governor of Puerto Rico

Abstract

The analysis of public sentiment is an invaluable tool in political campaigns, enabling candidates and their teams to assess voter attitudes and adjust campaign strategies accordingly. This project focuses on collecting and analyzing video comments on YouTube from the months leading up to an election to determine the public’s sentiment toward different candidates for governor in Puerto Rico. To make this sentiment analysis, the Text Blob Python library was used due to its ease of use and robust functionality. The project incorporates both client-side and server-side components, integrating modern web development frameworks and libraries to provide good user experience. This investigation outlines the data collection methodology, system architecture, analysis process, discussion of results, and coding logic used to achieve the analysis. Key Terms ⎯ Political Campaigns, Sentiment Analysis, TextBlob Python Library.