mlsanityData to 7 Oct 2026

Graph Neural Networks for Text Classification: A Survey

arXiv 2304.11534 ↗First posted 23 Apr 2023cs.CLcited by 15

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Abstract (arXiv)

Text Classification is the most essential and fundamental problem in Natural Language Processing. While numerous recent text classification models applied the sequential deep learning technique, graph neural network-based models can directly deal with complex structured text data and exploit global information. Many real text classification applications can be naturally cast into a graph, which captures words, documents, and corpus global features. In this survey, we bring the coverage of methods up to 2023, including corpus-level and document-level graph neural networks. We discuss each of these methods in detail, dealing with the graph construction mechanisms and the graph-based learning process. As well as the technological survey, we look at issues behind and future directions addressed in text classification using graph neural networks. We also cover datasets, evaluation metrics, and experiment design and present a summary of published performance on the publicly available benchmarks. Note that we present a comprehensive comparison between different techniques and identify the pros and cons of various evaluation metrics in this survey.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 63 of its 149 references that are in the map. First posted on arXiv 23 Apr 2023.

Builds on

63 of 149 references.

References · 63

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  4. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  5. 2017Graph Attention Networkscited by 8,854
  6. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,530
  7. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  8. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,016
  9. 2017Neural Message Passing for Quantum Chemistrycited by 3,460
  10. 2019A Comprehensive Survey on Graph Neural Networkscited by 2,906
  11. 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,341
  12. 2015Character-level Convolutional Networks for Text Classificationcited by 2,293
38 more
  1. 2018Deep contextualized word representationscited by 2,285
  2. 2016Enriching Word Vectors with Subword Informationcited by 1,578
  3. 2018Graph Neural Networks: A Review of Methods and Applicationscited by 1,571
  4. 2019Simplifying Graph Convolutional Networkscited by 1,470
  5. 2016Variational Graph Auto-Encoderscited by 1,373
  6. 2018Relational inductive biases, deep learning, and graph networkscited by 1,341
  7. 2020Making Pre-trained Language Models Better Few-shot Learnerscited by 1,255
  8. 2014Convolutional Neural Networks for Sentence Classificationcited by 1,124
  9. 2016Geometric deep learning: going beyond Euclidean datacited by 1,042
  10. 2015Gated Graph Sequence Neural Networkscited by 792
  11. 2018Hierarchical Graph Representation Learning with Differentiable Poolingcited by 786
  12. 2017Automated Hate Speech Detection and the Problem of Offensive Languagecited by 724
  13. 2021GPT Understands, Toocited by 715
  14. 2014Distributed Representations of Sentences and Documentscited by 677
  15. 2017Representation Learning on Graphs: Methods and Applicationscited by 456
  16. 2018Graph Convolutional Networks for Text Classificationcited by 345
  17. 2016Learning Convolutional Neural Networks for Graphscited by 314
  18. 2015Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networkscited by 305
  19. 2018Large Scale Crowdsourcing and Characterization of Twitter Abusive Behaviorcited by 265
  20. 2020Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddingscited by 212
  21. 2021Self-Supervised Learning of Graph Neural Networks: A Unified Reviewcited by 184
  22. 2014A Convolutional Neural Network for Modelling Sentencescited by 163
  23. 2019Text Classification Algorithms: A Surveycited by 163
  24. 2016Recurrent Neural Network for Text Classification with Multi-Task Learningcited by 144
  25. 2020Deep Learning Based Text Classification: A Comprehensive Reviewcited by 140
  26. 2020Foundations and modelling of dynamic networks using Dynamic Graph Neural Networks: A surveycited by 123
  27. 2018Attention-based Graph Neural Network for Semi-supervised Learningcited by 100
  28. 2020A Survey on Text Classification: From Shallow to Deep Learningcited by 80
  29. 2020Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networkscited by 77
  30. 2021A Review on Graph Neural Network Methods in Financial Applicationscited by 77
  31. 2021BertGCN: Transductive Text Classification by Combining GCN and BERTcited by 74
  32. 2020Be More with Less: Hypergraph Attention Networks for Inductive Text Classificationcited by 73
  33. 2021A Review of Graph Neural Networks and Their Applications in Power Systemscited by 62
  34. 2019Text Level Graph Neural Network for Text Classificationcited by 60
  35. 2022Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunitiescited by 52
  36. 2020Tensor Graph Convolutional Networks for Text Classificationcited by 49
  37. 2015Natural Language Inference by Tree-Based Convolution and Heuristic Matchingcited by 42
  38. 2020VGCN-BERT: Augmenting BERT with Graph Embedding for Text Classificationcited by 35

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Citing papers per year: 2024: 4; 2025: 3; 2026: 8.

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  1. 2024Graph Contrastive Learning via Cluster-refined Negative Sampling for Semi-supervised Text Classificationcited by 8
  2. 2025Large Language Models Meet Text-Attributed Graphs: A Survey of Integration Frameworks and Applicationscited by 5
  3. 2025MCP-Orchestrated Multi-Agent System for Automated Disinformation Detectioncited by 4
  4. 2024DocNet: Semantic Structure in Inductive Bias Detection Modelscited by 0
  5. 2024A Structural Feature-Based Approach for Comprehensive Graph Classificationcited by 0
  6. 2024PQ-GCN: Enhancing Text Graph Question Classification with Phrase Featurescited by 0
  7. 2025Text2Graph: Combining Lightweight LLMs and GNNs for Efficient Text Classification in Label-Scarce Scenarioscited by 0
  8. 2026From Global to Local: Learning Context-Aware Graph Representations for Document Classification and Summarizationcited by 0
  9. 2026CLiGNet: Clinical Label-Interaction Graph Network for Medical Specialty Classification from Clinical Transcriptionscited by 0
  10. 2026Robustness of Graph Self-Supervised Learning to Real-World Noise: A Case Study on Text-Driven Biomedical Graphscited by 0
  11. 2026HyperPersona: A Multi-Level Hypergraph Framework for Text-Based Automatic Personality Predictioncited by 0
  12. 2026Invariant-Based Weight Sharing for Message Passingcited by 0
3 more
  1. 2026Domain-Agnostic Neural Topic Modeling with Contextual Token-Level Semantic Graph Representationcited by 0
  2. 2026Relational Over-Regularization: Graph-Based AI-Generated Text Detection via Sentence Transition Deviationcited by 0
  3. 2026Low resource cross-modal alignment using HGNN to enhance speech representationcited by 0