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Deep Learning for Sentiment Analysis : A Survey

arXiv 1801.07883 ↗First posted 24 Jan 2018cs.CL cs.IR cs.LGcited by 139

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Abstract (arXiv)

Deep learning has emerged as a powerful machine learning technique that learns multiple layers of representations or features of the data and produces state-of-the-art prediction results. Along with the success of deep learning in many other application domains, deep learning is also popularly used in sentiment analysis in recent years. This paper first gives an overview of deep learning and then provides a comprehensive survey of its current applications in sentiment analysis.

Key facts. Cited by 139 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Jan 2018.

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Citing papers per year: 2021: 25; 2022: 38; 2023: 36; 2024: 21; 2025: 14; 2026: 5.

139 papers.

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  1. 2024Benchmark Data Contamination of Large Language Models: A Surveycited by 138
  2. 2022Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLPcited by 99
  3. 2023Is ChatGPT a Good Sentiment Analyzer? A Preliminary Studycited by 96
  4. 2023Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and Toxicitycited by 86
  5. 2024Bias in Large Language Models: Origin, Evaluation, and Mitigationcited by 77
  6. 2024Natural Language Understanding and Inference with MLLM in Visual Question Answering: A Surveycited by 74
  7. 2023Advancing Transformer Architecture in Long-Context Large Language Models: A Comprehensive Surveycited by 71
  8. 2023AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languagescited by 68
  9. 2022A Survey on Aspect-Based Sentiment Analysis: Tasks, Methods, and Challengescited by 61
  10. 2021Affective Image Content Analysis: Two Decades Review and New Perspectivescited by 47
  11. 2023SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval)cited by 41
  12. 2026Maximum Likelihood Reinforcement Learningcited by 29
38 more
  1. 2022FedAdapter: Efficient Federated Learning for Modern NLPcited by 24
  2. 2023LLMind: Orchestrating AI and IoT with LLM for Complex Task Executioncited by 24
  3. 2021Ethics Sheet for Automatic Emotion Recognition and Sentiment Analysiscited by 22
  4. 2023Rationalization for Explainable NLP: A Surveycited by 22
  5. 2022CLMLF:A Contrastive Learning and Multi-Layer Fusion Method for Multimodal Sentiment Detectioncited by 21
  6. 2022On Distributed Adaptive Optimization with Gradient Compressioncited by 19
  7. 2022Affection: Learning Affective Explanations for Real-World Visual Datacited by 19
  8. 2021COVID-19 sentiment analysis via deep learning during the rise of novel casescited by 18
  9. 2022Knowledge Graph Augmented Network Towards Multiview Representation Learning for Aspect-based Sentiment Analysiscited by 16
  10. 2022Instruction Tuning for Few-Shot Aspect-Based Sentiment Analysiscited by 16
  11. 2023LAraBench: Benchmarking Arabic AI with Large Language Modelscited by 16
  12. 2022A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Predictionscited by 15
  13. 2022Federated Few-Shot Learning for Mobile NLPcited by 15
  14. 2021HeBERT & HebEMO: a Hebrew BERT Model and a Tool for Polarity Analysis and Emotion Recognitioncited by 14
  15. 2021A Concise Review of Transfer Learningcited by 13
  16. 2021LTD: Low Temperature Distillation for Gradient Masking-free Adversarial Trainingcited by 13
  17. 2024Human-like Affective Cognition in Foundation Modelscited by 13
  18. 2023The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysiscited by 12
  19. 2021Understand me, if you refer to Aspect Knowledge: Knowledge-aware Gated Recurrent Memory Networkcited by 11
  20. 2021TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labelscited by 11
  21. 2022BiSyn-GAT+: Bi-Syntax Aware Graph Attention Network for Aspect-based Sentiment Analysiscited by 11
  22. 2023Sentiment Analysis through LLM Negotiationscited by 11
  23. 2025Affective Image Editing: Shaping Emotional Factors via Text Descriptionscited by 11
  24. 2021An AutoML-based Approach to Multimodal Image Sentiment Analysiscited by 9
  25. 2021First Target and Opinion then Polarity: Enhancing Target-opinion Correlation for Aspect Sentiment Triplet Extractioncited by 8
  26. 2021A Survey on sentiment analysis in Persian: A Comprehensive System Perspective Covering Challenges and Advances in Resources, and Methodscited by 8
  27. 2021Multistage linguistic conditioning of convolutional layers for speech emotion recognitioncited by 8
  28. 2023ChatGPT-Like Large-Scale Foundation Models for Prognostics and Health Management: A Survey and Roadmapscited by 8
  29. 2023SentiGOLD: A Large Bangla Gold Standard Multi-Domain Sentiment Analysis Dataset and its Evaluationcited by 8
  30. 2023Do Generative Large Language Models need billions of parameters?cited by 8
  31. 2023Deep Prompt Tuning for Graph Transformerscited by 8
  32. 2025A Simple Ensemble Strategy for LLM Inference: Towards More Stable Text Classificationcited by 8
  33. 2021Computational Emotion Analysis From Images: Recent Advances and Future Directionscited by 6
  34. 2022A Review on Text-Based Emotion Detection -- Techniques, Applications, Datasets, and Future Directionscited by 6
  35. 2023An evaluation of Google Translate for Sanskrit to English translation via sentiment and semantic analysiscited by 6
  36. 2023Think Rationally about What You See: Continuous Rationale Extraction for Relation Extractioncited by 6
  37. 2023L3Cube-MahaSent-MD: A Multi-domain Marathi Sentiment Analysis Dataset and Transformer Modelscited by 6
  38. 2023USA: Universal Sentiment Analysis Model & Construction of Japanese Sentiment Text Classification and Part of Speech Datasetcited by 6

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