mlsanityData to 14 Oct 2026

Enhancing Granular Sentiment Classification with Chain-of-Thought Prompting in Large Language Models

arXiv 2505.04135 ↗First posted 7 May 2025cs.CL cs.LGcited by 0

On the map: LLM reasoning → Prompting and chain-of-thought reasoning

Abstract (arXiv)

We explore the use of Chain-of-Thought (CoT) prompting with large language models (LLMs) to improve the accuracy of granular sentiment categorization in app store reviews. Traditional numeric and polarity-based ratings often fail to capture the nuanced sentiment embedded in user feedback. We evaluated the effectiveness of CoT prompting versus simple prompting on 2000 Amazon app reviews by comparing each method's predictions to human judgements. CoT prompting improved classification accuracy from 84% to 93% highlighting the benefit of explicit reasoning in enhancing sentiment analysis performance.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Prompting and chain-of-thought reasoning, one of 17 directions in LLM reasoning. Builds on 6 of its 12 references that are in the map. First posted on arXiv 7 May 2025.

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6 of 12 references.

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Same direction, newest first

  1. 2023Controllable Data Augmentation for Few-Shot Text Mining with Chain-of-Thought Attribute Manipulation14 Jul
  2. 2022Large Language Models are Zero-Shot Reasoners24 May
  3. 2022Least-to-Most Prompting Enables Complex Reasoning in Large Language Models21 May
  4. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Models28 Jan

Other references · 2

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2024How Effectively Do LLMs Extract Feature-Sentiment Pairs from App Reviews?cited by 2

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  1. 2023Enhance Multi-domain Sentiment Analysis of Review Texts through Prompting Strategies
  2. 2025Exploring Zero-Shot ACSA with Unified Meaning Representation in Chain-of-Thought Prompting
  3. 2023Analyzing Chain-of-Thought Prompting in Large Language Models via Gradient-based Feature Attributions
  4. 2025Reassessing the Role of Chain-of-Thought in Sentiment Analysis: Insights and Limitations
  5. 2025Beyond Stars: Bridging the Gap Between Ratings and Review Sentiment with LLM
  6. 2026Evaluating LLM Usage for Efficient and Explainable Numerical and Classified Implicit Sentiment Analysis of Product Desirability
  7. 2025How does Chain of Thought Think? Mechanistic Interpretability of Chain-of-Thought Reasoning with Sparse Autoencoding
  8. 2025Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs