Analyzing Bot Activity and Political Discourse in the 2024 U.S. Presidential Election: A Machine Learning Approach to Misinformation and Manipulation

Social media has become a battleground for political discourse, with automated accounts (bots) playing a growing role in shaping public opinion and engagement. In the context of the 2024 U.S. Presidential Election, understanding bot activity is crucial for identifying potential misinformation and manipulation tactics. This study analyzes 50,191 tweets collected between May and July 2023 to assess bot prevalence and influence. Bot detection is conducted using Botometer API scores and a Random Forest Regressor (MSE: 0.0071, R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>: 0.779), facilitating a multi-threshold analysis. Findings indicate a low overall bot presence (2.22% at a 0.7 threshold) but significant variations across political affiliations. While human-generated content dominates with a 15:1 engagement ratio, bots are most effective in cross-party discussions (engagement ratio: 0.145), whereas Democratic-focused bots exhibit the lowest engagement success. To deepen insights into election-related influence operations, a novel party-affiliation analysis framework is introduced, shedding light on platform-specific manipulation strategies and their implications for political discourse.