survey

Multimodal Sentiment Analysis: A Survey of Methods, Trends, and Challenges

Authors:

Thoudam Doren SinghAuthors Info & Claims

ACM Computing Surveys, Volume 55, Issue 13s

Article No.: 270, Pages 1 - 38

https://doi.org/10.1145/3586075

Published: 13 July 2023 Publication History

Abstract

Sentiment analysis has come long way since it was introduced as a natural language processing task nearly 20 years ago. Sentiment analysis aims to extract the underlying attitudes and opinions toward an entity. It has become a powerful tool used by governments, businesses, medicine, marketing, and others. The traditional sentiment analysis model focuses mainly on text content. However, technological advances have allowed people to express their opinions and feelings through audio, image and video channels. As a result, sentiment analysis is shifting from unimodality to multimodality. Multimodal sentiment analysis brings new opportunities with the rapid increase of sentiment analysis as complementary data streams enable improved and deeper sentiment detection which goes beyond text-based analysis. Audio and video channels are included in multimodal sentiment analysis in terms of broadness. People have been working on different approaches to improve sentiment analysis system performance by employing complex deep neural architectures. Recently, sentiment analysis has achieved significant success using the transformer-based model. This paper presents a comprehensive study of different sentiment analysis approaches, applications, challenges, and resources then concludes that it holds tremendous potential. The primary motivation of this survey is to highlight changing trends in the unimodality to multimodality for solving sentiment analysis tasks.

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Index Terms

Multimodal Sentiment Analysis: A Survey of Methods, Trends, and Challenges
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Lexical semantics

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 55, Issue 13s

December 2023

1367 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3606252

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Albert Zomaya
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Published: 13 July 2023

Online AM: 01 March 2023

Accepted: 14 February 2023

Revised: 06 February 2023

Received: 05 June 2022

Published in CSUR Volume 55, Issue 13s

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