Multi-level Multiple Attentions for Contextual Multimodal Sentiment Analysis

Multimodal sentiment analysis involves identifying sentiment in videos and is a developing field of research. Unlike current works, which model utterances individually, we propose a recurrent model that is able to capture contextual information among utterances. In this paper, we also introduce atte...

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Bibliographic Details
Published inProceedings (IEEE International Conference on Data Mining) pp. 1033 - 1038
Main Authors Poria, Soujanya, Cambria, Erik, Hazarika, Devamanyu, Mazumder, Navonil, Zadeh, Amir, Morency, Louis-Philippe
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2017
Subjects
Context modeling
Feature extraction
Fuses
Sentiment analysis
Social network services
Videos
Visualization
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Summary:Multimodal sentiment analysis involves identifying sentiment in videos and is a developing field of research. Unlike current works, which model utterances individually, we propose a recurrent model that is able to capture contextual information among utterances. In this paper, we also introduce attentionbased networks for improving both context learning and dynamic feature fusion. Our model shows 6-8% improvement over the state of the art on a benchmark dataset.
ISSN:2374-8486
DOI:10.1109/ICDM.2017.134