mlsanityData to 14 Oct 2026

Sentiment Analysis in the Era of Large Language Models: A Reality Check

arXiv 2305.15005 ↗First posted 24 May 2023cs.CLcited by 268

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Abstract (arXiv)

Sentiment analysis (SA) has been a long-standing research area in natural language processing. It can offer rich insights into human sentiments and opinions and has thus seen considerable interest from both academia and industry. With the advent of large language models (LLMs) such as ChatGPT, there is a great potential for their employment on SA problems. However, the extent to which existing LLMs can be leveraged for different sentiment analysis tasks remains unclear. This paper aims to provide a comprehensive investigation into the capabilities of LLMs in performing various sentiment analysis tasks, from conventional sentiment classification to aspect-based sentiment analysis and multifaceted analysis of subjective texts. We evaluate performance across 13 tasks on 26 datasets and compare the results against small language models (SLMs) trained on domain-specific datasets. Our study reveals that while LLMs demonstrate satisfactory performance in simpler tasks, they lag behind in more complex tasks requiring deeper understanding or structured sentiment information. However, LLMs significantly outperform SLMs in few-shot learning settings, suggesting their potential when annotation resources are limited. We also highlight the limitations of current evaluation practices in assessing LLMs' SA abilities and propose a novel benchmark, textscSentiEval, for a more comprehensive and realistic evaluation. Data and code during our investigations are available at urlhttps://github.com/DAMO-NLP-SG/LLM-Sentiment.

Key facts. Cited by 268 papers in the map (data through 14 Oct 2026). Builds on 33 of its 77 references that are in the map. First posted on arXiv 24 May 2023.

Builds on

33 of 77 references.

References · 33

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21 more
  1. 2021Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivitycited by 1,135
  2. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitycited by 894
  3. 2023Instruction Tuning with GPT-4cited by 686
  4. 2020TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classificationcited by 417
  5. 2023Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyondcited by 411
  6. 2021True Few-Shot Learning with Language Modelscited by 344
  7. 2021Towards Emotional Support Dialog Systemscited by 299
  8. 2022UL2: Unifying Language Learning Paradigmscited by 295
  9. 2023A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Modelscited by 246
  10. 2019SemEval-2017 Task 4: Sentiment Analysis in Twittercited by 210
  11. 2019SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)cited by 207
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  14. 2021Aspect Sentiment Quad Prediction as Paraphrase Generationcited by 100
  15. 2023Is ChatGPT a Good Sentiment Analyzer? A Preliminary Studycited by 96
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  18. 2022A Survey on Aspect-Based Sentiment Analysis: Tasks, Methods, and Challengescited by 61
  19. 2021Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Trainingcited by 37
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 36; 2024: 93; 2025: 82; 2026: 57.

268 papers.

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  1. 2023A Survey on Evaluation of Large Language Modelscited by 1,242
  2. 2023Multilingual Jailbreak Challenges in Large Language Modelscited by 240
  3. 2024Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMscited by 229
  4. 2023Large Language Models in Finance: A Surveycited by 226
  5. 2023EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizerscited by 193
  6. 2024Benchmark Data Contamination of Large Language Models: A Surveycited by 147
  7. 2025LLM Post-Training: A Deep Dive into Reasoning Large Language Modelscited by 135
  8. 2024Large Language Models Meet NLP: A Surveycited by 103
  9. 2024Safeguarding Large Language Models: A Surveycited by 78
  10. 2023Unleashing the potential of prompt engineering for large language modelscited by 72
  11. 2023Thread of Thought Unraveling Chaotic Contextscited by 72
  12. 2024LLM Discussion: Enhancing the Creativity of Large Language Models via Discussion Framework and Role-Playcited by 66
38 more
  1. 2024CyberMetric: A Benchmark Dataset based on Retrieval-Augmented Generation for Evaluating LLMs in Cybersecurity Knowledgecited by 55
  2. 2023Probing LLMs for hate speech detection: strengths and vulnerabilitiescited by 52
  3. 2024Designing Heterogeneous LLM Agents for Financial Sentiment Analysiscited by 48
  4. 2024Harnessing the Power of Multiple Minds: Lessons Learned from LLM Routingcited by 46
  5. 2024HelloBench: Evaluating Long Text Generation Capabilities of Large Language Modelscited by 44
  6. 2023Exploring the Potential of Large Language Models in Computational Argumentationcited by 42
  7. 2024What is the Role of Small Models in the LLM Era: A Surveycited by 41
  8. 2025TimeXL: Explainable Multi-modal Time Series Prediction with LLM-in-the-Loopcited by 39
  9. 2024Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Modelscited by 36
  10. 2024Large Language Models as Markov Chainscited by 35
  11. 2023TCRA-LLM: Token Compression Retrieval Augmented Large Language Model for Inference Cost Reductioncited by 34
  12. 2023A Wide Evaluation of ChatGPT on Affective Computing Taskscited by 30
  13. 2023A Fast Optimization View: Reformulating Single Layer Attention in LLM Based on Tensor and SVM Trick, and Solving It in Matrix Multiplication Timecited by 30
  14. 2023DialogueLLM: Context and Emotion Knowledge-Tuned Large Language Models for Emotion Recognition in Conversationscited by 30
  15. 2024MatryoshkaKV: Adaptive KV Compression via Trainable Orthogonal Projectioncited by 29
  16. 2024Can Small Language Models be Good Reasoners for Sequential Recommendation?cited by 26
  17. 2024Context versus Prior Knowledge in Language Modelscited by 26
  18. 2023FFT: Towards Harmlessness Evaluation and Analysis for LLMs with Factuality, Fairness, Toxicitycited by 25
  19. 2024Affective Computing in the Era of Large Language Models: A Survey from the NLP Perspectivecited by 25
  20. 2024HOLMES: Hyper-Relational Knowledge Graphs for Multi-hop Question Answering using LLMscited by 24
  21. 2024DataGen: Unified Synthetic Dataset Generation via Large Language Modelscited by 23
  22. 2024The Price of Prompting: Profiling Energy Use in Large Language Models Inferencecited by 23
  23. 2025Jailbreak-AudioBench: In-Depth Evaluation and Analysis of Jailbreak Threats for Large Audio Language Modelscited by 23
  24. 2023LLM for SoC Security: A Paradigm Shiftcited by 22
  25. 2024Assessing Adversarial Robustness of Large Language Models: An Empirical Studycited by 21
  26. 2024From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalitiescited by 19
  27. 2024Understanding the Therapeutic Relationship between Counselors and Clients in Online Text-based Counseling using LLMscited by 19
  28. 2024Pragmatic Metacognitive Prompting Improves LLM Performance on Sarcasm Detectioncited by 19
  29. 2023MM-BigBench: Evaluating Multimodal Models on Multimodal Content Comprehension Taskscited by 18
  30. 2024Evaluating the Capabilities of Large Language Models for Multi-label Emotion Understandingcited by 17
  31. 2023Why Can Large Language Models Generate Correct Chain-of-Thoughts?cited by 16
  32. 2024Contextualized Sequence Likelihood: Enhanced Confidence Scores for Natural Language Generationcited by 16
  33. 2024Large Language Models Meet Text-Centric Multimodal Sentiment Analysis: A Surveycited by 16
  34. 2023Machine-assisted quantitizing designs: augmenting humanities and social sciences with artificial intelligencecited by 15
  35. 2023An Interdisciplinary Outlook on Large Language Models for Scientific Researchcited by 15
  36. 2025An overview of model uncertainty and variability in LLM-based sentiment analysis. Challenges, mitigation strategies and the role of explainabilitycited by 15
  37. 2025EEmo-Bench: A Benchmark for Multi-modal Large Language Models on Image Evoked Emotion Assessmentcited by 15
  38. 2025A Survey of Attacks on Large Language Modelscited by 15

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