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DialogueRNN: An Attentive RNN for Emotion Detection in Conversations

arXiv 1811.00405 ↗First posted 1 Nov 2018cs.CLcited by 218

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Abstract (arXiv)

Emotion detection in conversations is a necessary step for a number of applications, including opinion mining over chat history, social media threads, debates, argumentation mining, understanding consumer feedback in live conversations, etc. Currently, systems do not treat the parties in the conversation individually by adapting to the speaker of each utterance. In this paper, we describe a new method based on recurrent neural networks that keeps track of the individual party states throughout the conversation and uses this information for emotion classification. Our model outperforms the state of the art by a significant margin on two different datasets.

Key facts. Cited by 218 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Nov 2018.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 32; 2022: 39; 2023: 50; 2024: 36; 2025: 22; 2026: 39.

218 papers.

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  1. 2021MMGCN: Multimodal Fusion via Deep Graph Convolution Network for Emotion Recognition in Conversationcited by 99
  2. 2021Directed Acyclic Graph Network for Conversational Emotion Recognitioncited by 97
  3. 2022GCNet: Graph Completion Network for Incomplete Multimodal Learning in Conversationcited by 87
  4. 2021DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in Conversationscited by 71
  5. 2021Topic-Driven and Knowledge-Aware Transformer for Dialogue Emotion Detectioncited by 56
  6. 2023Is ChatGPT Equipped with Emotional Dialogue Capabilities?cited by 54
  7. 2023Towards Interpretable Mental Health Analysis with Large Language Modelscited by 53
  8. 2022MM-DFN: Multimodal Dynamic Fusion Network for Emotion Recognition in Conversationscited by 52
  9. 2021Attention, please! A survey of Neural Attention Models in Deep Learningcited by 51
  10. 2022M3ED: Multi-modal Multi-scene Multi-label Emotional Dialogue Databasecited by 50
  11. 2022EmoCaps: Emotion Capsule based Model for Conversational Emotion Recognitioncited by 48
  12. 2022M2FNet: Multi-modal Fusion Network for Emotion Recognition in Conversationcited by 47
38 more
  1. 2023Deep Imbalanced Learning for Multimodal Emotion Recognition in Conversationscited by 47
  2. 2023A Transformer-Based Model With Self-Distillation for Multimodal Emotion Recognition in Conversationscited by 37
  3. 2021CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in Conversationcited by 35
  4. 2021Multi-modal Sarcasm Detection and Humor Classification in Code-mixed Conversationscited by 33
  5. 2023MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learningcited by 33
  6. 2024Revisiting Multi-modal Emotion Learning with Broad State Space Models and Probability-guidance Fusioncited by 33
  7. 2024Revisiting Multimodal Emotion Recognition in Conversation from the Perspective of Graph Spectrumcited by 33
  8. 2023A Comprehensive Survey on Multi-modal Conversational Emotion Recognition with Deep Learningcited by 32
  9. 2022Supervised Prototypical Contrastive Learning for Emotion Recognition in Conversationcited by 31
  10. 2022WOODS: Benchmarks for Out-of-Distribution Generalization in Time Seriescited by 30
  11. 2023DialogueLLM: Context and Emotion Knowledge-Tuned Large Language Models for Emotion Recognition in Conversationscited by 30
  12. 2022COGMEN: COntextualized GNN based Multimodal Emotion recognitioNcited by 29
  13. 2023A Low-rank Matching Attention based Cross-modal Feature Fusion Method for Conversational Emotion Recognitioncited by 29
  14. 2021Graph Based Network with Contextualized Representations of Turns in Dialoguecited by 26
  15. 2022CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AIcited by 26
  16. 2024MIntRec2.0: A Large-scale Benchmark Dataset for Multimodal Intent Recognition and Out-of-scope Detection in Conversationscited by 26
  17. 2021Hybrid Curriculum Learning for Emotion Recognition in Conversationcited by 25
  18. 2023DER-GCN: Dialogue and Event Relation-Aware Graph Convolutional Neural Network for Multimodal Dialogue Emotion Recognitioncited by 23
  19. 2024Efficient Long-distance Latent Relation-aware Graph Neural Network for Multi-modal Emotion Recognition in Conversationscited by 23
  20. 2022Tailor Versatile Multi-modal Learning for Multi-label Emotion Recognitioncited by 22
  21. 2024Advancing Social Intelligence in AI Agents: Technical Challenges and Open Questionscited by 22
  22. 2021EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue Systemscited by 20
  23. 2022GraphCFC: A Directed Graph Based Cross-Modal Feature Complementation Approach for Multimodal Conversational Emotion Recognitioncited by 20
  24. 2021RESPER: Computationally Modelling Resisting Strategies in Persuasive Conversationscited by 19
  25. 2023Supervised Adversarial Contrastive Learning for Emotion Recognition in Conversationscited by 19
  26. 2024Masked Graph Learning with Recurrent Alignment for Multimodal Emotion Recognition in Conversationcited by 19
  27. 2023Conversation Understanding using Relational Temporal Graph Neural Networks with Auxiliary Cross-Modality Interactioncited by 18
  28. 2021A Survey on Deep Reinforcement Learning for Audio-Based Applicationscited by 17
  29. 2023UniSA: Unified Generative Framework for Sentiment Analysiscited by 17
  30. 2021DADgraph: A Discourse-aware Dialogue Graph Neural Network for Multiparty Dialogue Machine Reading Comprehensioncited by 16
  31. 2021Dyadformer: A Multi-modal Transformer for Long-Range Modeling of Dyadic Interactionscited by 16
  32. 2022Knowledge-Bridged Causal Interaction Network for Causal Emotion Entailmentcited by 16
  33. 2023Refashioning Emotion Recognition Modelling: The Advent of Generalised Large Modelscited by 16
  34. 2021Automatically Select Emotion for Response via Personality-affected Emotion Transitioncited by 15
  35. 2022MSCTD: A Multimodal Sentiment Chat Translation Datasetcited by 15
  36. 2023Think Twice: A Human-like Two-stage Conversational Agent for Emotional Response Generationcited by 14
  37. 2023Cluster-Level Contrastive Learning for Emotion Recognition in Conversationscited by 14
  38. 2023CFN-ESA: A Cross-Modal Fusion Network with Emotion-Shift Awareness for Dialogue Emotion Recognitioncited by 14

50 most cited of 218 All 218 (JSON)