Ensemble transfer learning-based multimodal sentiment analysis using weighted convolutional neural networks
Huge amounts of multimodal content and comments in a mixture form of text, image, and
emoji are continuously shared by users on various social networks. Most of the comments of …
emoji are continuously shared by users on various social networks. Most of the comments of …
A cognitive brain model for multimodal sentiment analysis based on attention neural networks
Multimodal sentiment analysis is one of the most attractive interdisciplinary research topics
in artificial intelligence (AI). Different from other classification issues, multimodal sentiment …
in artificial intelligence (AI). Different from other classification issues, multimodal sentiment …
A comprehensive survey on deep learning-based approaches for multimodal sentiment analysis
A Ghorbanali, MK Sohrabi - Artificial Intelligence Review, 2023 - Springer
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 …
A soft voting ensemble learning-based approach for multimodal sentiment analysis
It is possible to determine people's feelings and opinions about a subject or product from
social media posts via sentiment analysis. With the pervasive usage of the Internet and …
social media posts via sentiment analysis. With the pervasive usage of the Internet and …
Sentiment-aware multimodal pre-training for multimodal sentiment analysis
Pre-trained models, together with fine-tuning on downstream labeled datasets, have
demonstrated great success in various tasks, including multimodal sentiment analysis …
demonstrated great success in various tasks, including multimodal sentiment analysis …
Attention-based sentiment analysis using convolutional and recurrent neural network
M Usama, B Ahmad, E Song, MS Hossain… - Future Generation …, 2020 - Elsevier
Convolution and recurrent neural network have obtained remarkable performance in natural
language processing (NLP). Moreover, from the attention mechanism perspective …
language processing (NLP). Moreover, from the attention mechanism perspective …
Co-LSTM: Convolutional LSTM model for sentiment analysis in social big data
Abstract Analysis of consumer reviews posted on social media is found to be essential for
several business applications. Consumer reviews posted in social media are increasing at …
several business applications. Consumer reviews posted in social media are increasing at …
A fine-grained modal label-based multi-stage network for multimodal sentiment analysis
Sentiment analysis is a challenging but valuable research topic in affective computing. It can
improve the quality of various real-world applications, including financial market prediction …
improve the quality of various real-world applications, including financial market prediction …
BAFN: Bi-direction attention based fusion network for multimodal sentiment analysis
Attention-based networks currently identify their effectiveness in multimodal sentiment
analysis. However, existing methods ignore the redundancy of auxiliary modalities. More …
analysis. However, existing methods ignore the redundancy of auxiliary modalities. More …
TEDT: transformer-based encoding–decoding translation network for multimodal sentiment analysis
F Wang, S Tian, L Yu, J Liu, J Wang, K Li… - Cognitive Computation, 2023 - Springer
Multimodal sentiment analysis is a popular and challenging research topic in natural
language processing, but the impact of individual modal data in videos on sentiment …
language processing, but the impact of individual modal data in videos on sentiment …