MINING AND TEXT ANALYSIS OF SOCIAL MEDIA DATA FOR IMPROVED DECISION MAKING (FOCUS: POLITICAL CASE STUDY ON THE SENATE PRESIDENT AND SENATOR NATASHA AKPOTI-UDUAGHAN CONFLICT)

This project explores the application of mining and text analysis techniques on social media data to aid in improved decision-making, focusing on a political context. Specifically, it investigates public reactions, sentiments, and narratives surrounding the political conflict between the Senate President and Senator Natasha Akpoti-Uduaghan. Social media platforms have become significant tools for expressing political opinions, and analyzing such content can provide insights into public perception and societal trends. Using tools like sentiment analysis and data mining, this project evaluates social media discussions to understand regional responses, misinformation trends, and dominant political narratives. This case study demonstrates how technology can support political analysis and decision-making by revealing hidden patterns in large volumes of social discourse. The findings of this project show how computational techniques can enhance political monitoring, support transparency, and inform strategic decisions by political stakeholders. The work underscores the importance of interdisciplinary approaches that combine computer science, linguistics, and political science for real-world impact.