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 …
Progress, achievements, and challenges in multimodal sentiment analysis using deep learning: A survey
A Pandey, DK Vishwakarma - Applied Soft Computing, 2024 - Elsevier
Sentiment analysis is a computational technique that analyses the subjective information
conveyed within a given expression. This encompasses appraisals, opinions, attitudes or …
conveyed within a given expression. This encompasses appraisals, opinions, attitudes or …
Progress of IoT research technologies and applications serving Hajj and Umrah
The term IoT technology is associated with many fields, including scientific, commercial,
industrial, health, transportation and other fields, which became a necessity of daily life …
industrial, health, transportation and other fields, which became a necessity of daily life …
Tag-assisted multimodal sentiment analysis under uncertain missing modalities
Multimodal sentiment analysis has been studied under the assumption that all modalities
are available. However, such a strong assumption does not always hold in practice, and …
are available. However, such a strong assumption does not always hold in practice, and …
A comprehensive survey on deep learning-based approaches for multimodal sentiment analysis
Sentiment analysis is an important natural language processing issue that has many
applications in various fields. The increasing popularity of social networks and growth and …
applications in various fields. The increasing popularity of social networks and growth and …
Multi-level graph neural network for text sentiment analysis
Text sentiment analysis is a fundamental task in the field of natural language processing
(NLP). Recently, graph neural networks (GNNs) have achieved excellent performance in …
(NLP). Recently, graph neural networks (GNNs) have achieved excellent performance in …
Multimodal sentiment analysis: A survey
Multimodal sentiment analysis has emerged as a prominent research field within artificial
intelligence, benefiting immensely from recent advancements in deep learning. This …
intelligence, benefiting immensely from recent advancements in deep learning. This …
Multimodal sentiment analysis representations learning via contrastive learning with condense attention fusion
H Wang, X Li, Z Ren, M Wang, C Ma - Sensors, 2023 - mdpi.com
Multimodal sentiment analysis has gained popularity as a research field for its ability to
predict users' emotional tendencies more comprehensively. The data fusion module is a …
predict users' emotional tendencies more comprehensively. The data fusion module is a …
A deep multi-level attentive network for multimodal sentiment analysis
Multimodal sentiment analysis has attracted increasing attention with broad application
prospects. Most of the existing methods have focused on a single modality, which fails to …
prospects. Most of the existing methods have focused on a single modality, which fails to …
Integrating big data driven sentiments polarity and ABC-optimized LSTM for time series forecasting
Stock market is a dynamic and volatile market that is considered as time series data. The
growth of financial data exposed the computational efficiency of the conventional systems …
growth of financial data exposed the computational efficiency of the conventional systems …