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Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions
Sentiment analysis (SA) has gained much traction In the field of artificial intelligence (AI) and
natural language processing (NLP). There is growing demand to automate analysis of user …
natural language processing (NLP). There is growing demand to automate analysis of user …
A survey on sentiment analysis methods, applications, and challenges
The rapid growth of Internet-based applications, such as social media platforms and blogs,
has resulted in comments and reviews concerning day-to-day activities. Sentiment analysis …
has resulted in comments and reviews concerning day-to-day activities. Sentiment analysis …
Multimodal sentiment analysis based on fusion methods: A survey
Sentiment analysis is an emerging technology that aims to explore people's attitudes toward
an entity. It can be applied in a variety of different fields and scenarios, such as product …
an entity. It can be applied in a variety of different fields and scenarios, such as product …
Multimodal sentiment analysis: a survey of methods, trends, and challenges
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 …
processing task nearly 20 years ago. Sentiment analysis aims to extract the underlying …
A comprehensive survey on sentiment analysis: Approaches, challenges and trends
Sentiment analysis (SA), also called Opinion Mining (OM) is the task of extracting and
analyzing people's opinions, sentiments, attitudes, perceptions, etc., toward different entities …
analyzing people's opinions, sentiments, attitudes, perceptions, etc., toward different entities …
[HTML][HTML] Recent advancements and challenges of NLP-based sentiment analysis: A state-of-the-art review
Sentiment analysis is a method within natural language processing that evaluates and
identifies the emotional tone or mood conveyed in textual data. Scrutinizing words and …
identifies the emotional tone or mood conveyed in textual data. Scrutinizing words and …
Sentiment analysis using deep learning architectures: a review
Social media is a powerful source of communication among people to share their sentiments
in the form of opinions and views about any topic or article, which results in an enormous …
in the form of opinions and views about any topic or article, which results in an enormous …
Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review
In recent years, the rapid advances in machine learning (ML) and information fusion has
made it possible to endow machines/computers with the ability of emotion understanding …
made it possible to endow machines/computers with the ability of emotion understanding …
Soybean yield prediction from UAV using multimodal data fusion and deep learning
Preharvest crop yield prediction is critical for grain policy making and food security. Early
estimation of yield at field or plot scale also contributes to high-throughput plant phenoty** …
estimation of yield at field or plot scale also contributes to high-throughput plant phenoty** …
Machine learning algorithms for social media analysis: A survey
Social Media (SM) are the most widespread and rapid data generation applications on the
Internet increase the study of these data. However, the efficient processing of such massive …
Internet increase the study of these data. However, the efficient processing of such massive …