Implicit Sentiment Analysis Based on Chain of Thought Prompting
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Abstract (arXiv)
Implicit Sentiment Analysis (ISA) is a crucial research area in natural language processing. Inspired by the idea of large language model Chain of Thought (CoT), this paper introduces a Sentiment Analysis of Thinking (SAoT) framework. The framework first analyzes the implicit aspects and opinions in the text using common sense and thinking chain capabilities. Then, it reflects on the process of implicit sentiment analysis and finally deduces the polarity of sentiment. The model is evaluated on the SemEval 2014 dataset, consisting of 1120 restaurant reviews and 638 laptop reviews. The experimental results demonstrate that the utilization of the ERNIE-Bot-4+SAoT model yields a notable performance improvement. Specifically, on the restaurant dataset, the F1 score reaches 75.27, accompanied by an ISA score of 66.29. Similarly, on the computer dataset, the F1 score achieves 76.50, while the ISA score amounts to 73.46. Comparatively, the ERNIE-Bot-4+SAoT model surpasses the BERTAsp + SCAPt baseline by an average margin of 47.99%.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 8 of its 10 references that are in the map. First posted on arXiv 22 Aug 2024.
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8 of 10 references.
References · 8
- 2017Attention Is All You Needcited by 59,932
- 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
- 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
- 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
- 2022MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoningcited by 153
- 2023Reasoning Implicit Sentiment with Chain-of-Thought Promptingcited by 79
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.
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- 2025Application of Multiple Chain-of-Thought in Contrastive Reasoning for Implicit Sentiment Analysis
- 2025Causal Prompting for Implicit Sentiment Analysis with Large Language Models
- 2025Reassessing the Role of Chain-of-Thought in Sentiment Analysis: Insights and Limitations
- 2023Enhance Multi-domain Sentiment Analysis of Review Texts through Prompting Strategies
- 2024RVISA: Reasoning and Verification for Implicit Sentiment Analysis
- 2026Large-Scale Aspect-Based Sentiment Analysis with Reasoning-Infused LLMs
- 2024Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning
- 2025Exploring Zero-Shot ACSA with Unified Meaning Representation in Chain-of-Thought Prompting