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Multimodal Sentiment Analysis: A Survey and Comparison

Author

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  • Ramandeep Kaur

    (Guru Kashi University, Talwandi Sabo, India)

  • Sandeep Kautish

    (Guru Kashi University, Talwandi Sabo, India)

Abstract

Multimodal sentiments have become the challenge for the researchers and are equally sophisticated for an appliance to understand. One of the studies that support MS problems is a MSA, which is the training of emotions, attitude, and opinion from the audiovisual format. This survey article covers the comprehensive overview of the last update in this field. Many recently proposed algorithms and various MSA applications are presented briefly in this survey. The article is categorized according to their contributions in the various MSA techniques. The main purpose of this survey is to provide a full image of the MSA opportunities and difficulties and related field with brief details. The main contribution of this article includes the sophisticated categorizations of a large number of recent articles and the illustration of the recent trend of research in the MSA and its related areas.

Suggested Citation

  • Ramandeep Kaur & Sandeep Kautish, 2019. "Multimodal Sentiment Analysis: A Survey and Comparison," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 10(2), pages 38-58, April.
    • Handle: RePEc:igg:jssmet:v:10:y:2019:i:2:p:38-58
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    Cited by:

    1. Brahami Menaouer & Abdeldjouad Fatma Zahra & Sabri Mohammed, 2022. "Multi-Class Sentiment Classification for Healthcare Tweets Using Supervised Learning Techniques," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 13(1), pages 1-23, January.

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