<![CDATA[Ethiopia's political landscape, characterized by ethnic federalism and the National Dialogue process, faces escalating polarization amplified by TikTok's algorithmically curated content. Traditional machine learning approaches struggle to capture the quantum-like dynamics of political discourse, superposition of identities, entanglement of ethnic and ideological factors, and context-dependent meaning. This study introduces the first quantum-enhanced multimodal framework for analyzing political discourse on Ethiopian TikTok, integrating quantum entanglement-driven fake news detection (Q-ALIGNer), quantum LSTM sentiment analysis, and quantum frequency-based opinion shift modeling (OpinionXf). We developed a hybrid quantum-classical pipeline processing 50,000 Amharic, Oromo, Tigrinya, and English TikTok videos. Q-ALIGNer encodes text, video, and audio modalities as quantum states with entanglement-based fusion. Quantum LSTM captures temporal sentiment evolution, while OpinionXf models opinion shifts using frequency-domain transformations. Performance was evaluated against classical baselines using 10-fold cross-validation. Q-ALIGNER achieved 92.5% accuracy, outperforming classical models by 8.2–13.9%, with only 4.6% accuracy drop under adversarial attack versus 11.9% for classical models. Quantum LSTM achieved 89.7% accuracy with 15.2% MAE reduction over AfriBERTa. Sarcasm detection improved by 8.4% and coded political language by 9.1%. OpinionXf achieved 85.7% precision and 100% recall for 72-hour early warning, detecting shifts 3–6 days before classical models. Ablation study revealed quantum layers contributed 46.3% and entanglement 53.7% of total performance gain. Entanglement-based similarity maps revealed three political actor clusters with intra-cluster entanglement 0.85–0.92 versus inter-cluster 0.65–0.72. Quantum-enhanced frameworks significantly improve detection of misinformation, sentiment polarization, and opinion shifts in Ethiopian political discourse, enabling proactive early warning systems. Deploy the 3-layer quantum model with all-to-all entanglement for Ethiopia's National Dialogue Commission, prioritizing high-persuadability local issues while approaching identity-based topics through deliberative processes.]]>
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