Sentiment Analysis of Political Tweets During the 2024 Presidential Election

In Fall 2024, the Marketing team analyzed a large dataset of political tweets related to the 2024 U.S. Presidential election. The project involved processing extensive CSV files, each containing tens of thousands of tweets and an array of metadata. The primary focus was on the textual content of tweets that mentioned one or both presidential candidates. Using OpenAI’s API, the team conducted sentiment analysis across the datasets, creating a combined database of over 500,000 sentiment-scored tweets. This enabled the construction of time-series plots to visualize sentiment trends for each candidate as the election approached. Methods such as simple moving averages were applied to highlight significant shifts in public opinion as captured through the lens of Twitter/X. Future efforts will aim to leverage the remaining metadata to generate more nuanced visualizations, exploring correlations with geographic, temporal, and user-related variables. The team also plans to develop an interactive GUI featuring advanced visualization tools to empower users to dynamically explore and interpret the dataset, paving the way for broader applications in social media analytics.