mlsanityData to 7 Oct 2026

Graph Neural Networks: a bibliometrics overview

arXiv 2201.01188 ↗First posted 3 Jan 2022cs.LG cs.AI cs.DLcited by 5

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Abstract (arXiv)

Recently, graph neural networks have become a hot topic in machine learning community. This paper presents a Scopus based bibliometric overview of the GNNs research since 2004, when GNN papers were first published. The study aims to evaluate GNN research trend, both quantitatively and qualitatively. We provide the trend of research, distribution of subjects, active and influential authors and institutions, sources of publications, most cited documents, and hot topics. Our investigations reveal that the most frequent subject categories in this field are computer science, engineering, telecommunications, linguistics, operations research and management science, information science and library science, business and economics, automation and control systems, robotics, and social sciences. In addition, the most active source of GNN publications is Lecture Notes in Computer Science. The most prolific or impactful institutions are found in the United States, China, and Canada. We also provide must read papers and future directions. Finally, the application of graph convolutional networks and attention mechanism are now among hot topics of GNN research.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 53 of its 181 references that are in the map. First posted on arXiv 3 Jan 2022.

Builds on

53 of 181 references.

References · 53

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  4. 2017Graph Attention Networkscited by 8,854
  5. 2017Neural Message Passing for Quantum Chemistrycited by 3,460
  6. 2016node2vec: Scalable Feature Learning for Networkscited by 1,913
  7. 2017Modeling Relational Data with Graph Convolutional Networkscited by 1,684
  8. 2018Graph Neural Networks: A Review of Methods and Applicationscited by 1,571
  9. 2014DeepWalk: Online Learning of Social Representationscited by 1,543
  10. 2016Variational Graph Auto-Encoderscited by 1,373
  11. 2018Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognitioncited by 1,199
  12. 2018Graph Convolutional Neural Networks for Web-Scale Recommender Systemscited by 1,133
38 more
  1. 2017Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecastingcited by 1,125
  2. 2016Geometric deep learning: going beyond Euclidean datacited by 1,042
  3. 2015Gated Graph Sequence Neural Networkscited by 792
  4. 2014Distributed Representations of Sentences and Documentscited by 677
  5. 2019Neural Graph Collaborative Filteringcited by 660
  6. 2019Measuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological Viewcited by 544
  7. 2016Geometric deep learning on graphs and manifolds using mixture model CNNscited by 468
  8. 2018Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generationcited by 363
  9. 2019Multi-Label Image Recognition with Graph Convolutional Networkscited by 320
  10. 2018Graph R-CNN for Scene Graph Generationcited by 296
  11. 2019Actional-Structural Graph Convolutional Networks for Skeleton-based Action Recognitioncited by 228
  12. 2018Exploring Visual Relationship for Image Captioningcited by 215
  13. 2017State-of-the-art Speech Recognition With Sequence-to-Sequence Modelscited by 196
  14. 2019Events-to-Video: Bringing Modern Computer Vision to Event Camerascited by 191
  15. 2018Zero-shot Recognition via Semantic Embeddings and Knowledge Graphscited by 155
  16. 2020A Semi-supervised Graph Attentive Network for Financial Fraud Detectioncited by 150
  17. 2018Graph Convolution over Pruned Dependency Trees Improves Relation Extractioncited by 146
  18. 2020Structural Deep Clustering Networkcited by 145
  19. 2017Encoding Sentences with Graph Convolutional Networks for Semantic Role Labelingcited by 137
  20. 2019Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentencecited by 121
  21. 2019Edge-labeling Graph Neural Network for Few-shot Learningcited by 114
  22. 2020Heterogeneous Graph Neural Networks for Malicious Account Detectioncited by 95
  23. 2019DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classificationcited by 59
  24. 2019Spam Review Detection with Graph Convolutional Networkscited by 57
  25. 2019Missing Data Imputation with Adversarially-trained Graph Convolutional Networkscited by 54
  26. 2019Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Predictioncited by 54
  27. 2019Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphscited by 53
  28. 2019Label Efficient Semi-Supervised Learning via Graph Filteringcited by 46
  29. 2019Rethinking the Item Order in Session-based Recommendation with Graph Neural Networkscited by 43
  30. 2018Attention Models in Graphs: A Surveycited by 41
  31. 2020TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Networkcited by 37
  32. 2019A Context-Aware Citation Recommendation Model with BERT and Graph Convolutional Networkscited by 28
  33. 2020Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Appscited by 23
  34. 2019Modeling Sentiment Dependencies with Graph Convolutional Networks for Aspect-level Sentiment Classificationcited by 13
  35. 2019A Hierarchical Location Prediction Neural Network for Twitter User Geolocationcited by 11
  36. 2019Point Clouds Learning with Attention-based Graph Convolution Networkscited by 8
  37. 2019Dynamic Joint Variational Graph Autoencoderscited by 8
  38. 2020Graph Neural Networks-based Clustering for Social Internet of Thingscited by 7

50 most cited of 53 All 53 (JSON)

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Cited by year

Citing papers per year: 2022: 1; 2023: 3; 2024: 1.

5 papers.

  1. 2023Using ChatGPT as a Static Application Security Testing Toolcited by 8
  2. 2023Examining the Effects of Degree Distribution and Homophily in Graph Learning Modelscited by 5
  3. 2023Graph Neural Ordinary Differential Equations-based method for Collaborative Filteringcited by 5
  4. 2024GNN Applied to Ego-nets for Friend Suggestionscited by 1
  5. 2022Multi-view graph structure learning using subspace merging on Grassmann manifoldcited by 0