# Graph Neural Network Framework for Sentiment Analysis Using Syntactic Feature

arXiv: https://arxiv.org/abs/2409.14000 · HTML: https://mlsanity.com/paper/2409.14000/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 23 references that are in the map.
- First posted on arXiv 21 Sep 2024.

## Builds on (most cited first, 11 of 11)

- [NDC-Scene: Boost Monocular 3D Semantic Scene Completion in Normalized Device Coordinates Space](https://mlsanity.com/paper/2309.14616/) (2023)
- [Survival Prediction Across Diverse Cancer Types Using Neural Networks](https://mlsanity.com/paper/2404.08713/) (2024)
- [Research on Adverse Drug Reaction Prediction Model Combining Knowledge Graph Embedding and Deep Learning](https://mlsanity.com/paper/2407.16715/) (2024)
- [Adaptive Friction in Deep Learning: Enhancing Optimizers with Sigmoid and Tanh Function](https://mlsanity.com/paper/2408.11839/) (2024)
- [A comparative study of generative adversarial networks for image recognition algorithms based on deep learning and traditional methods](https://mlsanity.com/paper/2408.03568/) (2024)
- [Dynamic Hypergraph-Enhanced Prediction of Sequential Medical Visits](https://mlsanity.com/paper/2408.07084/) (2024)
- [Algorithm Research of ELMo Word Embedding and Deep Learning Multimodal Transformer in Image Description](https://mlsanity.com/paper/2408.06357/) (2024)
- [Applying Conditional Generative Adversarial Networks for Imaging Diagnosis](https://mlsanity.com/paper/2408.02074/) (2024)
- [Text classification optimization algorithm based on graph neural network](https://mlsanity.com/paper/2408.15257/) (2024)
- [Enhancing Convolutional Neural Networks with Higher-Order Numerical Difference Methods](https://mlsanity.com/paper/2409.04977/) (2024)
- [Enhancing Deep Learning with Optimized Gradient Descent: Bridging Numerical Methods and Neural Network Training](https://mlsanity.com/paper/2409.04707/) (2024)

## Built on by (most cited first, 6 of 6)

- [Self-Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks](https://mlsanity.com/paper/2410.17617/) (2024)
- [Optimizing YOLOv5s Object Detection through Knowledge Distillation algorithm](https://mlsanity.com/paper/2410.12259/) (2024)
- [Adversarial Neural Networks in Medical Imaging Advancements and Challenges in Semantic Segmentation](https://mlsanity.com/paper/2410.13099/) (2024)
- [Automated Genre-Aware Article Scoring and Feedback Using Large Language Models](https://mlsanity.com/paper/2410.14165/) (2024)
- [Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis](https://mlsanity.com/paper/2410.24046/) (2024)
- [Optimizing Retrieval-Augmented Generation with Elasticsearch for Enhanced Question-Answering Systems](https://mlsanity.com/paper/2410.14167/) (2024)

## Abstract (arXiv)

Amidst the swift evolution of social media platforms and e-commerce ecosystems, the domain of opinion mining has surged as a pivotal area of exploration within natural language processing. A specialized segment within this field focuses on extracting nuanced evaluations tied to particular elements within textual contexts. This research advances a composite framework that amalgamates the positional cues of topical descriptors. The proposed system converts syntactic structures into a matrix format, leveraging convolutions and attention mechanisms within a graph to distill salient characteristics. Incorporating the positional relevance of descriptors relative to lexical items enhances the sequential integrity of the input. Trials have substantiated that this integrated graph-centric scheme markedly elevates the efficacy of evaluative categorization, showcasing preeminence.