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| A Survey on Multimodal Sentiment Analysis |
| ZHANG Yazhou1, RONG Lu2, SONG Dawei3, ZHANG Peng4 |
1. College of Software Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002;
2. Personnel Department, Zhengzhou University of Light Industry, Zhengzhou 450002;
3. School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081;
4. College of Intelligence and Computing, Tianjin University, Tianjin 300350 |
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Abstract Multimodal sentiment analysis is one of the core research topics in the field of natural language processing. Firstly, the research background of multimodal sentiment analysis is introduced. Two sub-topics of multimodal sentiment analysis, narrative multimodal sentiment analysis and interactive multimodal sentiment analysis, are proposed. Then, the development and the research progress at home and abroad are summarized based on the mentioned two sub-topics. Finally, the existing scientific problems of interactive modeling in this field are summarized, and the future development trend is discussed.
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Received: 31 December 2019
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| Fund:Supported by National Key Research and Development Program of China(No.2018YFC0831704), National Natural Science Foundation of China(No.U1636203,61772363,U1736103), Major Project of Zhejiang Laboratory(No.2019DH0ZX01), European Union's Horizon 2020 Research and Innovation Program under the Marie Skodowska-Curie Grant Agreement(No.721321) |
| About author:: (ZHANG Yazhou, Ph.D., lecturer. His research interests include multimodal sentiment analysis, natural language processing and quantum cognition.);(RONG Lu, master, research assistant. Her research interests include natural language understanding, machine translation and computational language.);(SONG Dawei(Corresponding author), Ph.D., professor. His research interests include information retrieval, natural language processing and quantum cognition.);(ZHANG Peng, Ph.D., associate profe-ssor. His research interests include information retrieval, natural language processing and quantum cognition.) |
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2020, Vol. 33 
