The research paper Explainable Sentiment Analysis with DeepSeek-R1: Performance, Efficiency, and Few-Shot Learning demonstrates that DeepSeek-R1, a reasoning-based, open-source AI model, achieves near state-of-the-art sentiment analysis accuracy while providing transparent, step-by-step explanations of its decisions. Unlike black-box models such as GPT-4, DeepSeek-R1 combines interpretability with efficiency, delivering over 90% accuracy using only a fraction of the computational resources. For business leaders, this marks a pivotal shift: organizations can now adopt explainable AI systems that meet compliance, auditing, and ethical governance standards without relying on proprietary vendors. The study highlights a maturing AI ecosystem where transparent reasoning and cost efficiency become as valuable as raw performance, key factors for AI adoption in regulated or trust-sensitive industries.

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Key point: This paper shows that DeepSeek-R1 delivers high-accuracy, explainable sentiment analysis with far greater efficiency than GPT-4, proving that open-source reasoning models can achieve transparent, cost-effective, and trustworthy AI performance at scale.