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Multimodal Sentiment Analysis: A Survey of Methods, Trends, and Challenges
ACM Computing Surveys ( IF 16.6 ) Pub Date : 2023-07-13 , DOI: 10.1145/3586075
Ringki Das, Thoudam Doren Singh

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.



中文翻译:

多模态情感分析:方法、趋势和挑战的调查

自从近 20 年前作为自然语言处理任务引入以来,情感分析已经取得了长足的进步。情感分析旨在提取对实体的潜在态度和意见。它已成为政府、企业、医药、营销等领域使用的强大工具。传统的情感分析模型主要关注文本内容。然而,技术进步使人们可以通过音频、图像和视频渠道表达自己的意见和感受。因此,情感分析正在从单模态转向多模态。随着情感分析的快速增长,多模态情感分析带来了新的机遇,因为互补的数据流可以改进和更深入的情感检测,超越基于文本的分析。就广度而言,音频和视频通道都包含在多模态情感分析中。人们一直在研究不同的方法,通过采用复杂的深度神经架构来提高情感分析系统的性能。最近,使用基于变压器的模型进行情感分析取得了巨大的成功。本文对不同的情感分析方法、应用、挑战和资源进行了全面研究,然后得出结论,它具有巨大的潜力。这项调查的主要动机是强调解决情感分析任务的单模态到多模态的变化趋势。使用基于变压器的模型进行情感分析取得了巨大的成功。本文对不同的情感分析方法、应用、挑战和资源进行了全面研究,然后得出结论,它具有巨大的潜力。这项调查的主要动机是强调解决情感分析任务的单模态到多模态的变化趋势。使用基于变压器的模型进行情感分析取得了巨大的成功。本文对不同的情感分析方法、应用、挑战和资源进行了全面研究,然后得出结论,它具有巨大的潜力。这项调查的主要动机是强调解决情感分析任务的单模态到多模态的变化趋势。

更新日期:2023-07-13
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