mlsanityData to 13 Oct 2026

Sentiment Analysis Based on Deep Learning: A Comparative Study

arXiv 2006.03541 ↗First posted 5 Jun 2020cs.CL cs.IR cs.LGcited by 37

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Abstract (arXiv)

The study of public opinion can provide us with valuable information. The analysis of sentiment on social networks, such as Twitter or Facebook, has become a powerful means of learning about the users' opinions and has a wide range of applications. However, the efficiency and accuracy of sentiment analysis is being hindered by the challenges encountered in natural language processing (NLP). In recent years, it has been demonstrated that deep learning models are a promising solution to the challenges of NLP. This paper reviews the latest studies that have employed deep learning to solve sentiment analysis problems, such as sentiment polarity. Models using term frequency-inverse document frequency (TF-IDF) and word embedding have been applied to a series of datasets. Finally, a comparative study has been conducted on the experimental results obtained for the different models and input features

Key facts. Cited by 37 papers in the map (data through 13 Oct 2026). First posted on arXiv 5 Jun 2020.

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Citing papers per year: 2021: 3; 2022: 6; 2023: 9; 2024: 13; 2025: 4; 2026: 2.

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  1. 2023Evaluating the Social Impact of Generative AI Systems in Systems and Societycited by 91
  2. 2024AI Companions Reduce Lonelinesscited by 28
  3. 2022A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Predictionscited by 15
  4. 2024Turning Generative Models Degenerate: The Power of Data Poisoning Attackscited by 9
  5. 2021Sentiment Classification in Swahili Language Using Multilingual BERTcited by 6
  6. 2023An evaluation of Google Translate for Sanskrit to English translation via sentiment and semantic analysiscited by 6
  7. 2024SYNTHEVAL: Hybrid Behavioral Testing of NLP Models with Synthetic CheckListscited by 6
  8. 2023Sentiment Analysis in Finance: From Transformers Back to eXplainable Lexicons (XLex)cited by 5
  9. 2021Jointly Modeling Aspect and Polarity for Aspect-based Sentiment Analysis in Persian Reviewscited by 4
  10. 2024Using LLMs to Establish Implicit User Sentiment of Software Desirabilitycited by 4
  11. 2023Can Model Fusing Help Transformers in Long Document Classification? An Empirical Studycited by 3
  12. 2022Domain Adaptation of Transformer-Based Models using Unlabeled Data for Relevance and Polarity Classification of German Customer Feedbackcited by 2
25 more
  1. 2024Exploring Ordinality in Text Classification: A Comparative Study of Explicit and Implicit Techniquescited by 2
  2. 2024Dynamic Adaptive Optimization for Effective Sentiment Analysis Fine-Tuning on Large Language Modelscited by 2
  3. 2022Transfer Learning with Joint Fine-Tuning for Multimodal Sentiment Analysiscited by 1
  4. 2022Retrieving Users' Opinions on Social Media with Multimodal Aspect-Based Sentiment Analysiscited by 1
  5. 2023LaFiCMIL: Rethinking Large File Classification from the Perspective of Correlated Multiple Instance Learningcited by 1
  6. 2024LLM-Assisted Content Conditional Debiasing for Fair Text Embeddingcited by 1
  7. 2024Decoding Emotions in Abstract Art: Cognitive Plausibility of CLIP in Recognizing Color-Emotion Associationscited by 1
  8. 2024OneLove beyond the field -- A few-shot pipeline for topic and sentiment analysis during the FIFA World Cup in Qatarcited by 1
  9. 2024Artificial Intelligence in Landscape Architecture: A Surveycited by 1
  10. 2025Longitudinal Abuse and Sentiment Analysis of Hollywood Movie Dialogues using Language Modelscited by 1
  11. 2025ExBigBang: A Dynamic Approach for Explainable Persona Classification through Contextualized Hybrid Transformer Analysiscited by 1
  12. 2021Towards Financial Sentiment Analysis in a South African Landscapecited by 0
  13. 2022Sentiment Analysis of Political Tweets for Israel using Machine Learningcited by 0
  14. 2022YouTube Ad View Sentiment Analysis using Deep Learning and Machine Learningcited by 0
  15. 2023Building RadiologyNET: Unsupervised annotation of a large-scale multimodal medical databasecited by 0
  16. 2023Debunking Disinformation: Revolutionizing Truth with NLP in Fake News Detectioncited by 0
  17. 2023Interpreting Sentiment Composition with Latent Semantic Treecited by 0
  18. 2023Robust Sentiment Analysis for Low Resource languages Using Data Augmentation Approaches: A Case Study in Marathicited by 0
  19. 2024Understanding Social Perception, Interactions, and Safety Aspects of Sidewalk Delivery Robots Using Sentiment Analysiscited by 0
  20. 2024COVID-19 Twitter Sentiment Classification Using Hybrid Deep Learning Model Based on Grid Search Methodologycited by 0
  21. 2024Sentiment Analysis of Cyberbullying Data in Social Mediacited by 0
  22. 2025Investigating the Impact of Rationales for LLMs on Natural Language Understandingcited by 0
  23. 2025Algerian Dialectcited by 0
  24. 2026A Comparative Analysis of Classical Machine Learning and Deep Learning Approaches for Sentiment Classification on IMDb Movie Reviewscited by 0
  25. 2026Evaluating LLM Usage for Efficient and Explainable Numerical and Classified Implicit Sentiment Analysis of Product Desirabilitycited by 0