Multimodal sentimental analysis for social media applications: A comprehensive review

G Chandrasekaran, TN Nguyen… - … Reviews: Data Mining …, 2021 - Wiley Online Library
The analysis of sentiments is essential in identifying and classifying opinions regarding a
source material that is, a product or service. The analysis of these sentiments finds a variety …

Hypergraph learning: Methods and practices

Y Gao, Z Zhang, H Lin, X Zhao, S Du… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Hypergraph learning is a technique for conducting learning on a hypergraph structure. In
recent years, hypergraph learning has attracted increasing attention due to its flexibility and …

[PDF][PDF] Dynamic hypergraph neural networks.

J Jiang, Y Wei, Y Feng, J Cao, Y Gao - IJCAI, 2019 - researchgate.net
In recent years, graph/hypergraph-based deep learning methods have attracted much
attention from researchers. These deep learning methods take graph/hypergraph structure …

Image-text multimodal emotion classification via multi-view attentional network

X Yang, S Feng, D Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Compared with single-modal content, multimodal data can express users' feelings and
sentiments more vividly and interestingly. Therefore, multimodal sentiment analysis has …

Emotion recognition from multiple modalities: Fundamentals and methodologies

S Zhao, G Jia, J Yang, G Ding… - IEEE Signal Processing …, 2021 - ieeexplore.ieee.org
Humans are emotional creatures. Multiple modalities are often involved when we express
emotions, whether we do so explicitly (such as through facial expression and speech) or …

Knowledge-aware multi-modal adaptive graph convolutional networks for fake news detection

S Qian, J Hu, Q Fang, C Xu - ACM Transactions on Multimedia …, 2021 - dl.acm.org
In this article, we focus on fake news detection task and aim to automatically identify the fake
news from vast amount of social media posts. To date, many approaches have been …

Confede: Contrastive feature decomposition for multimodal sentiment analysis

J Yang, Y Yu, D Niu, W Guo, Y Xu - … of the 61st Annual Meeting of …, 2023 - aclanthology.org
Abstract Multimodal Sentiment Analysis aims to predict the sentiment of video content.
Recent research suggests that multimodal sentiment analysis critically depends on learning …

A novel deep learning-based sentiment analysis method enhanced with emojis in microblog social networks

X Li, J Zhang, Y Du, J Zhu, Y Fan… - Enterprise Information …, 2023 - Taylor & Francis
To exactly classify sentiments of microblog reviews with emojis in microblog social networks,
this paper first proposes an emoji vectorisation method to achieve emoji vectors. Then, an …

A comprehensive review of visual–textual sentiment analysis from social media networks

IKS Al-Tameemi, MR Feizi-Derakhshi… - … of Computational Social …, 2024 - Springer
Social media networks have become a significant aspect of people's lives, serving as a
platform for their ideas, opinions and emotions. Consequently, automated sentiment …

Attention-based modality-gated networks for image-text sentiment analysis

F Huang, K Wei, J Weng, Z Li - ACM Transactions on Multimedia …, 2020 - dl.acm.org
Sentiment analysis of social multimedia data has attracted extensive research interest and
has been applied to many tasks, such as election prediction and products evaluation …