# Multi-channel Attentive Graph Convolutional Network With Sentiment Fusion For Multimodal Sentiment Analysis

arXiv: https://arxiv.org/abs/2201.10274 · HTML: https://mlsanity.com/paper/2201.10274/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 25 references that are in the map.
- First posted on arXiv 25 Jan 2022.

## Builds on (most cited first, 15 of 15)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Multimodal Machine Learning: A Survey and Taxonomy](https://mlsanity.com/paper/1705.09406/) (2017)
- [Tensor Fusion Network for Multimodal Sentiment Analysis](https://mlsanity.com/paper/1707.07250/) (2017)
- [Efficient Low-rank Multimodal Fusion with Modality-Specific Factors](https://mlsanity.com/paper/1806.00064/) (2018)
- [A Survey of Human-in-the-loop for Machine Learning](https://mlsanity.com/paper/2108.00941/) (2021)
- [MOSI: Multimodal Corpus of Sentiment Intensity and Subjectivity Analysis in Online Opinion Videos](https://mlsanity.com/paper/1606.06259/) (2016)
- [Learning Factorized Multimodal Representations](https://mlsanity.com/paper/1806.06176/) (2018)
- [Memory Fusion Network for Multi-view Sequential Learning](https://mlsanity.com/paper/1802.00927/) (2018)
- [Long Short-Term Memory-Networks for Machine Reading](https://mlsanity.com/paper/1601.06733/) (2016)
- [Found in Translation: Learning Robust Joint Representations by Cyclic Translations Between Modalities](https://mlsanity.com/paper/1812.07809/) (2018)
- [Attention Guided Graph Convolutional Networks for Relation Extraction](https://mlsanity.com/paper/1906.07510/) (2019)
- [SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis](https://mlsanity.com/paper/2005.05635/) (2020)
- [Multimodal Language Analysis with Recurrent Multistage Fusion](https://mlsanity.com/paper/1808.03920/) (2018)
- [Gated Mechanism for Attention Based Multimodal Sentiment Analysis](https://mlsanity.com/paper/2003.01043/) (2020)
- [A Multi-sentiment-resource Enhanced Attention Network for Sentiment Classification](https://mlsanity.com/paper/1807.04990/) (2018)

## Built on by (most cited first, 2 of 2)

- [Semantic2Graph: Graph-based Multi-modal Feature Fusion for Action Segmentation in Videos](https://mlsanity.com/paper/2209.05653/) (2022)
- [Exploring Multimodal Sentiment Analysis via CBAM Attention and Double-layer BiLSTM Architecture](https://mlsanity.com/paper/2303.14708/) (2023)

## Abstract (arXiv)

Nowadays, with the explosive growth of multimodal reviews on social media platforms, multimodal sentiment analysis has recently gained popularity because of its high relevance to these social media posts. Although most previous studies design various fusion frameworks for learning an interactive representation of multiple modalities, they fail to incorporate sentimental knowledge into inter-modality learning. This paper proposes a Multi-channel Attentive Graph Convolutional Network (MAGCN), consisting of two main components: cross-modality interactive learning and sentimental feature fusion. For cross-modality interactive learning, we exploit the self-attention mechanism combined with densely connected graph convolutional networks to learn inter-modality dynamics. For sentimental feature fusion, we utilize multi-head self-attention to merge sentimental knowledge into inter-modality feature representations. Extensive experiments are conducted on three widely-used datasets. The experimental results demonstrate that the proposed model achieves competitive performance on accuracy and F1 scores compared to several state-of-the-art approaches.