mlsanityData to 14 Oct 2026

Multimodal Sentiment Analysis: A Survey

arXiv 2305.07611 ↗First posted 12 May 2023cs.CL cs.CVcited by 12

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Abstract (arXiv)

Multimodal sentiment analysis has become an important research area in the field of artificial intelligence. With the latest advances in deep learning, this technology has reached new heights. It has great potential for both application and research, making it a popular research topic. This review provides an overview of the definition, background, and development of multimodal sentiment analysis. It also covers recent datasets and advanced models, emphasizing the challenges and future prospects of this technology. Finally, it looks ahead to future research directions. It should be noted that this review provides constructive suggestions for promising research directions and building better performing multimodal sentiment analysis models, which can help researchers in this field.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 16 of its 80 references that are in the map. First posted on arXiv 12 May 2023.

Builds on

16 of 80 references.

References · 16

  1. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,234
  2. 2018MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversationscited by 643
  3. 2020MISA: Modality-Invariant and -Specific Representations for Multimodal Sentiment Analysiscited by 265
  4. 2016MOSI: Multimodal Corpus of Sentiment Intensity and Subjectivity Analysis in Online Opinion Videoscited by 194
  5. 2021Learning Modality-Specific Representations with Self-Supervised Multi-Task Learning for Multimodal Sentiment Analysiscited by 180
  6. 2018Found in Translation: Learning Robust Joint Representations by Cyclic Translations Between Modalitiescited by 149
  7. 2018Words Can Shift: Dynamically Adjusting Word Representations Using Nonverbal Behaviorscited by 89
  8. 2018Multimodal Language Analysis with Recurrent Multistage Fusioncited by 44
  9. 2020Jointly Fine-Tuning "BERT-like" Self Supervised Models to Improve Multimodal Speech Emotion Recognitioncited by 38
  10. 2016Select-Additive Learning: Improving Generalization in Multimodal Sentiment Analysiscited by 29
  11. 2021The Multimodal Sentiment Analysis in Car Reviews (MuSe-CaR) Dataset: Collection, Insights and Improvementscited by 22
  12. 2022Vision Transformers in Medical Computer Vision -- A Contemplative Retrospectioncited by 22
4 more
  1. 2022Hybrid Multimodal Feature Extraction, Mining and Fusion for Sentiment Analysiscited by 12
  2. 2019Complementary Fusion of Multi-Features and Multi-Modalities in Sentiment Analysiscited by 11
  3. 2019Multimodal Emotion Classificationcited by 10
  4. 2021An AutoML-based Approach to Multimodal Image Sentiment Analysiscited by 9

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 7; 2025: 3; 2026: 1.

12 papers.

  1. 2024LR-FPN: Enhancing Remote Sensing Object Detection with Location Refined Feature Pyramid Networkcited by 27
  2. 2023Shared and Private Information Learning in Multimodal Sentiment Analysis with Deep Modal Alignment and Self-supervised Multi-Task Learningcited by 9
  3. 2024Part-Attention Based Model Make Occluded Person Re-Identification Strongercited by 5
  4. 2024DRIVE: Dependable Robust Interpretable Visionary Ensemble Framework in Autonomous Drivingcited by 5
  5. 2025Towards Explainable Fusion and Balanced Learning in Multimodal Sentiment Analysiscited by 3
  6. 2024PEPL: Precision-Enhanced Pseudo-Labeling for Fine-Grained Image Classification in Semi-Supervised Learningcited by 2
  7. 2024AdaFSNet: Time Series Classification Based on Convolutional Network with a Adaptive and Effective Kernel Size Configurationcited by 1
  8. 2024Improving the Classification Effect of Clinical Images of Diseases for Multi-Source Privacy Protectioncited by 1
  9. 2024S2RC-GCN: A Spatial-Spectral Reliable Contrastive Graph Convolutional Network for Complex Land Cover Classification Using Hyperspectral Imagescited by 0
  10. 2025Differential Attention for Multimodal Crisis Event Analysiscited by 0
  11. 2025Multi-Modal Sentiment Analysis with Dynamic Attention Fusioncited by 0
  12. 2026Unveiling Public Opinion: A Study of Sentiment Analysis Using LSTM and Traditional Modelscited by 0