Soujanya Poria · Singapore University of Technology and Design

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Works256 from public data

TitleCited by

Recent Trends in Deep Learning Based Natural Language Processing [Review Article]
IEEE Computational Intelligence Magazine · 2018
3,110
Tensor Fusion Network for Multimodal Sentiment Analysis
Conference on Empirical Methods in Natural Language Processing (EMNLP) · 2017
1,995
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
Annual Meeting of the Association for Computational Linguistics (ACL) · 2019
1,809
Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph
Annual Meeting of the Association for Computational Linguistics (ACL) · 2018
1,809
A review of affective computing: From unimodal analysis to multimodal fusion
Information Fusion · 2017
1,643
MISA
ACM International Conference on Multimedia (ACM MM) · 2020
1,392
Recent Trends in Deep Learning Based Natural Language Processing
arXiv · 2017
1,226
DialogueRNN: An Attentive RNN for Emotion Detection in Conversations
Proceedings of the AAAI Conference on Artificial Intelligence · 2019
1,046
Memory Fusion Network for Multi-view Sequential Learning
Proceedings of the AAAI Conference on Artificial Intelligence · 2018
991
Context-Dependent Sentiment Analysis in User-Generated Videos
Annual Meeting of the Association for Computational Linguistics (ACL) · 2017
914
Aspect extraction for opinion mining with a deep convolutional neural network
Knowledge-Based Systems · 2016
873
Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions
Information Fusion · 2022
781
DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation
Deepanway Ghosal, Navonil Majumder, Soujanya Poria, Niyati Chhaya, Alexander Gelbukh
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · 2019
725
Deep Learning-Based Document Modeling for Personality Detection from Text
IEEE Intelligent Systems · 2017
681
Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis
Conference on Empirical Methods in Natural Language Processing (EMNLP) · 2021
676
Convolutional MKL Based Multimodal Emotion Recognition and Sentiment Analysis
Proceedings · 2016
602
Multi-attention Recurrent Network for Human Communication Comprehension
Proceedings of the AAAI Conference on Artificial Intelligence · 2018
591
Deep Convolutional Neural Network Textual Features and Multiple Kernel Learning for Utterance-level Multimodal Sentiment Analysis
Conference on Empirical Methods in Natural Language Processing (EMNLP) · 2015
550
Enhanced SenticNet with Affective Labels for Concept-Based Opinion Mining
IEEE Intelligent Systems · 2013
509
Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances
IEEE Access · 2019
503
Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos
Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · 2018
494
SenticNet 6: Ensemble Application of Symbolic and Subsymbolic AI for Sentiment Analysis
Proceedings of the ... ACM International Conference on Information & Knowledge Management · 2020
466
ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection
Conference on Empirical Methods in Natural Language Processing (EMNLP) · 2018
458
COSMIC: COmmonSense knowledge for eMotion Identification in Conversations
Deepanway Ghosal, Navonil Majumder, Alexander Gelbukh, Rada Mihalcea, Soujanya Poria
Findings of the Association for Computational Linguistics: EMNLP 2020 · 2020
448
Sentiment Analysis Is a Big Suitcase
IEEE Intelligent Systems · 2017
441

Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-10. Citation counts may be lower than on Google Scholar, which indexes more sources.

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