TITLE:
Uganda Decides 2026: A Comprehensive Computational Analysis of Digital Political Discourse from January to November 2025
AUTHORS:
Samuel Ocen, Ritah Nafuna, Azizi Wasike
KEYWORDS:
Digital Political Landscape, Polarization, Natural Language Processing
JOURNAL NAME:
Journal of Data Analysis and Information Processing,
Vol.14 No.1,
January
12,
2026
ABSTRACT: This comprehensive longitudinal study analyzes Uganda’s digital political landscape throughout the critical pre-election year of 2025, examining 4.2 million social media posts collected from January 1 to November 10, 2025. Using advanced Natural Language Processing techniques, we identify eight dominant thematic clusters with significant temporal evolution, revealing how political discourse has shifted from constitutional debates (peak 38% in March) to economic crisis management (42% in October) and finally to security and electoral integrity concerns (35% in November). Sentiment analysis shows escalating polarization, with negative sentiment rising from 52% in January to 68% by November, concentrated around governance and economic issues. We document sophisticated AI-generated content campaigns comprising 14.3% of total volume and identify coordinated influence operations across six platforms. Network analysis reveals increasingly fragmented discourse ecosystems with minimal cross-ideological engagement. These findings provide unprecedented insights into Uganda’s evolving digital democracy and have critical implications for electoral integrity, political communication strategies, and democratic resilience in the 2026 elections.