BertGCN: Transductive Text Classification by Combining GNN and BERT

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) · doi:10.18653/v1/n19-1423 · Cited by 54,325

Statistical Learning Theory

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Semi-supervised classification with graph convolutional networks

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Graph Attention NetworksPreprint

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RoBERTa: A Robustly Optimized BERT Pretraining Approach

Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., & Stoyanov, V. (2019) · arXiv · doi:10.48550/arxiv.1907.11692 · Cited by 16,515

Convolutional Neural Networks for Sentence Classification

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Momentum Contrast for Unsupervised Visual Representation Learning

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Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reimers, N., & Gurevych, I. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · doi:10.18653/v1/d19-1410 · Cited by 12,778

Graph Attention Networks

Veličković, P., Cucurull, G., Casanova, A., Romero, A., Liò, P., & Bengio, Y. (2017) · arXiv · doi:10.48550/arxiv.1710.10903 · Cited by 12,107

Pre-Trained Language Models and Their Applications

Wang, H., Li, J., Wu, H. R., Hovy, E. H., & Sun, Y. (2022) · Engineering · doi:10.1016/j.eng.2022.04.024 · Cited by 435

A Survey on Text Classification Algorithms: From Text to Predictions

Gasparetto, A., Marcuzzo, M., Zangari, A., & Albarelli, A. (2022) · Information · doi:10.3390/info13020083 · Cited by 305

DeepBIO: an automated and interpretable deep-learning platform for high-throughput biological sequence prediction, functional annotation and visualization analysis

Wang, R., Jiang, Y., Jin, J., Yin, C., Yu, H., Wang, F., Feng, J., Su, R., Nakai, K., Zou, Q., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad055 · Cited by 178

CauseRec: Counterfactual User Sequence Synthesis for Sequential Recommendation

Zhang, S., Yao, D., Zhao, Z., Chua, T.-S., & Wu, F. (2021) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3404835.3462908 · Cited by 141

Hierarchical graph-based text classification framework with contextual node embedding and BERT-based dynamic fusion

Onan, A. (2023) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2023.101610 · Cited by 103

Graph neural networks for text classification: a survey

Wang, K., Ding, Y., & Han, S. C. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10808-0 · Cited by 108

InducT-GCN: Inductive Graph Convolutional Networks for Text Classification

Wang, K., Han, S. C., & Poon, J. (2022) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr56361.2022.9956075 · Cited by 73

Long short-term memory with activation on gradient

Qin, C., Chen, L., Cai, Z., Liu, M., & Jin, L. (2023) · Neural Networks · doi:10.1016/j.neunet.2023.04.026 · Cited by 69

Text FCG: Fusing Contextual Information via Graph Learning for text classification

Wang, Y., Wang, C., Zhan, J., Ma, W., & Jiang, Y. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.119658 · Cited by 52

Infusing Knowledge from Wikipedia to Enhance Stance Detection

He, Z., Mokhberian, N., & Lerman, K. (2022) · Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA) · doi:10.18653/v1/2022.wassa-1.7 · Cited by 52

Relational Graph Convolutional Network for Text-Mining-Based Accident Causal Classification

Chen, Z., Huang, K., Li, W., Zhong, Z., & Jiao, Z. (2022) · Applied Sciences · doi:10.3390/app12052482 · Cited by 40

Re-examining lexical and semantic attention: Dual-view graph convolutions enhanced BERT for academic paper rating

Xue, Z., He, G., Liu, J., Jiang, Z., Zhao, S. X., & Lu, W. (2022) · Information Processing & Management · doi:10.1016/j.ipm.2022.103216 · Cited by 34

Joint Learning With BERT-GCN and Multi-Attention for Event Text Classification and Event Assignment

She, X., Chen, J., & Chen, G. (2022) · IEEE Access · doi:10.1109/access.2022.3156918 · Cited by 34

Graph neural network–driven text classification for fire-door defect inspection in pre-completion construction

Wang, S. (2025) · Scientific Reports · doi:10.1038/s41598-025-28120-4 · Cited by 27

Transformer and Graph Convolutional Network for Text Classification

Liu, B., Guan, W., Yang, C., Fang, Z., & Lu, Z. (2023) · International Journal of Computational Intelligence Systems · doi:10.1007/s44196-023-00337-z · Cited by 29

Hierarchical Graph Convolutional Networks for Structured Long Document Classification

Liu, T., Hu, Y., Wang, B., Sun, Y., Gao, J., & Yin, B. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3185295 · Cited by 26

EHR-HGCN: An Enhanced Hybrid Approach for Text Classification Using Heterogeneous Graph Convolutional Networks in Electronic Health Records

Wang, G., Lou, X., Guo, F., Kwok, D., & Cao, C. (2023) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2023.3346210 · Cited by 25

Text Classification Using Graph Convolutional Networks: A Comprehensive Survey

Rizvi, S. M. H., Imran, R., & Mahmood, A. (2025) · ACM Computing Surveys · doi:10.1145/3714456 · Cited by 28

Contrastive learning from label distribution: A case study on text classification

Tao, Q., Li, F., Zhang, M., Jin, G., Fan, P., & Dai, W. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.07.076 · Cited by 21

Contrastive multi-graph learning with neighbor hierarchical sifting for semi-supervised text classification

Ai, W., Li, J., Wang, Z., Wei, Y., Meng, T., & Li, K. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125952 · Cited by 25

A Systematic Survey of Graph Convolutional Networks for Artificial Intelligence Applications

Sadasivan, A., Gananathan, K., Dhanith, P. R. J., & Surendiran, B. (2025) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.70012 · Cited by 21

Technology-Assisted Motivational Interviewing: Developing a Scalable Framework for Promoting Engagement with Tobacco Cessation Using NLP and Machine Learning

Saiyed, A., Layton, J. F., Borsari, B. E., Cheng, J., Kanzaveli, T., Tsvetovat, M., & Satterfield, J. M. (2022) · Procedia Computer Science · doi:10.1016/j.procs.2022.09.091 · Cited by 22

Predictive End-to-End Enterprise Process Network Monitoring

Oberdorf, F., Schaschek, M., Weinzierl, S., Stein, N., Matzner, M., & Flath, C. M. (2022) · Business & Information Systems Engineering · doi:10.1007/s12599-022-00778-4 · Cited by 26

Zero-Shot and Few-Shot Stance Detection on Varied Topics via Conditional Generation

Wen, H., & Hauptmann, A. G. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-short.127 · Cited by 20

A model of integrating convolution and BiGRU dual-channel mechanism for Chinese medical text classifications

Li, X., Zhang, Y., Jin, J., Sun, F., Li, N., & Liang, S. (2023) · PLoS ONE · doi:10.1371/journal.pone.0282824 · Cited by 19

A Multimodal Framework for the Identification of Vaccine Critical Memes on Twitter

Naseem, U., Kim, J., Khushi, M., & Dunn, A. G. (2023) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/3539597.3570450 · Cited by 19

Chain-of-Thought Embeddings for Stance Detection on Social Media

Gatto, J., Sharif, O., & Preum, S. M. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.273 · Cited by 21

A Heterogeneous Directed Graph Attention Network for inductive text classification using multilevel semantic embeddings

Lin, M., Wang, T., Zhu, Y., Li, X., Zhou, X., & Wang, W. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.111797 · Cited by 18

A distributable German clinical corpus containing cardiovascular clinical routine doctor’s letters

Richter-Pechanski, P., Wiesenbach, P., Schwab, D. M., Kiriakou, C., He, M., Allers, M. M., Tiefenbacher, A. S., Kunz, N., Martynova, A., Spiller, N., et al. (2023) · Scientific Data · doi:10.1038/s41597-023-02128-9 · Cited by 16

Simplified-Boosting Ensemble Convolutional Network for Text Classification

Zeng, F., Chen, N., Yang, D., & Meng, Z. (2022) · Neural Processing Letters · doi:10.1007/s11063-022-10843-4 · Cited by 15

Combining transformer-based model and GCN to predict ICD codes from clinical records

Lu, P., & Xue, J. (2023) · Knowledge-Based Systems · doi:10.1016/j.knosys.2023.111113 · Cited by 14

Bert-based graph unlinked embedding for sentiment analysis

Jin, Y., & Zhao, A. (2023) · Complex & Intelligent Systems · doi:10.1007/s40747-023-01289-9 · Cited by 14

Graph Receptive Transformer Encoder for Text Classification

Aras, A. C., Alikaşifoğlu, T., & Koç, A. (2024) · IEEE Transactions on Signal and Information Processing over Networks · doi:10.1109/tsipn.2024.3380362 · Cited by 14

Collaborative Knowledge Infusion for Low-Resource Stance Detection

Yan, M., Joey, T. Z., & Ivor, W. T. (2024) · Big Data Mining and Analytics · doi:10.26599/bdma.2024.9020021 · Cited by 14

MonaCoBERT: Monotonic Attention Based ConvBERT for Knowledge Tracing

Lee, U., Park, Y., Kim, Y., Choi, S., & Kim, H. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-63031-6_10 · Cited by 14

Case reports unlocked: Harnessing large language models to advance research on child maltreatment

Stoll, D., Wehrli, S., & Lätsch, D. (2024) · Child Abuse & Neglect · doi:10.1016/j.chiabu.2024.107202 · Cited by 16

BERT-GraphSAGE: hybrid approach to spam detection

Zouak, F., Beqqali, O. E., & Riffi, J. (2025) · Journal Of Big Data · doi:10.1186/s40537-025-01176-9 · Cited by 17

Penetrating the Hostile: Detecting DeFi Protocol Exploits Through Cross-Contract Analysis

Li, X., Li, W., Liu, Z., Zhang, Y., & Mao, Y. (2025) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2025.3626979 · Cited by 14

Transformers are Short-Text Classifiers

Karl, F., & Scherp, A. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-40837-3_7 · Cited by 15

CoGraphNet for enhanced text classification using word-sentence heterogeneous graph representations and improved interpretability

Li, P., Fu, X., Chen, J., & Hu, J. (2025) · Scientific Reports · doi:10.1038/s41598-024-83535-9 · Cited by 13

Contextualized Graph Embeddings for Adverse Drug Event Detection

Gao, Y., Ji, S., Zhang, T., Tiwari, P., & Marttinen, P. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-26390-3_35 · Cited by 12

Credit Scoring Prediction Using Deep Learning Models in the Financial Sector

Shi, X., Tang, D., & Yu, Y. (2025) · IEEE Access · doi:10.1109/access.2025.3591005 · Cited by 12

DTFL: A Digital Twin-Assisted Graph Neural Network Approach for Service Function Chains Failure Localization

Guo, K., Chen, J., Dong, P., Zou, T., Zhu, J., Huang, X., Liu, S., & Liao, C. (2023) · IEEE Transactions on Cloud Computing · doi:10.1109/tcc.2023.3294506 · Cited by 12

Dual-channel knowledge attention for traditional Chinese medicine syndrome differentiation

Liu, B., Huang, H., Liu, X., Zhao, J., & Mo, J. (2025) · Scientific Reports · doi:10.1038/s41598-025-96404-w · Cited by 10

TraitBertGCN: Personality Trait Prediction Using BertGCN with Data Fusion Technique

Waqas, M. M., Zhang, F., Laghari, A. A., Almadhor, A. S., Petrinec, F., Iqbal, A., & Khalil, M. M. Y. (2025) · International Journal of Computational Intelligence Systems · doi:10.1007/s44196-025-00792-w · Cited by 9

LMCBert: An Automatic Academic Paper Rating Model Based on Large Language Models and Contrastive Learning

Liu, C., Zhang, X., Zhao, H., Liu, Z., Xi, X., & Yu, L. (2025) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2025.3550203 · Cited by 10

Detecting sarcasm in user-generated content integrating transformers and gated graph neural networks

Qin, Z., Luo, Q., Zang, Z., & Fu, H. (2025) · PeerJ Computer Science · doi:10.7717/peerj-cs.2817 · Cited by 12

Attack Behavior Extraction Based on Heterogeneous Cyberthreat Intelligence and Graph Convolutional Networks

Tang, B., Wang, J., Qiu, H., Yu, J., Yu, Z., & Liu, S. (2022) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2023.029135 · Cited by 10

TextGCL: Graph Contrastive Learning for Transductive Text Classification

Zhao, Y., & Song, X. (2023) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn54540.2023.10191923 · Cited by 11

A novel model for relation prediction in knowledge graphs exploiting semantic and structural feature integration

Yang, J., Lu, G., He, S., Cao, Q., & Liu, Y. (2024) · Scientific Reports · doi:10.1038/s41598-024-63279-2 · Cited by 9

An effective multi-modal adaptive contextual feature information fusion method for Chinese long text classification

Xu, Y., Liu, G., Zhang, L., Shen, X., & Luo, S. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10835-x · Cited by 8

Software bug prediction using graph neural networks and graph-based text representations

Siachos, I., Kanakaris, N., & Karacapilidis, N. I. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125290 · Cited by 11

GazeGCN: Gaze-aware Graph Convolutional Network for Text Classification

Wang, B., Liang, B., Bai, Z., Yang, M., Gui, L., & Xu, R. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.128680 · Cited by 9

Graph-aware pre-trained language model for political sentiment analysis in Filipino social media

Aquino, J. A., Liew, D.-J., & Chang, Y. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.110317 · Cited by 10

Leveraging large language models for sentiment analysis: A hybrid contextual and linguistic feature fusion approach

Pha, L. A., & Tran, T. K. (2025) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2025.110643 · Cited by 8

PepGraphormer: an ESM-GAT hybrid deep learning framework for antimicrobial peptide prediction

Lin, C., Xiong, S., Li, J., Cui, F., Zhang, Z., Shi, H., & Wei, L. (2026) · Journal of Cheminformatics · doi:10.1186/s13321-025-01144-8 · Cited by 8

Continual Graph Convolutional Network for Text Classification

Wu, T., Liu, Q., Cao, Y., Huang, Y. T., Wu, X.-M., & Ding, J. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i11.26611 · Cited by 10

Knowledge-Graph- and GCN-Based Domain Chinese Long Text Classification Method

Wang, Y., Wang, Y., Hu, H., Zhou, S., & Wang, Q. (2023) · Applied Sciences · doi:10.3390/app13137915 · Cited by 8

TGCN-Bert Emoji Prediction in Information Systems Using TCN and GCN Fusing Features Based on BERT

Yang, Z., Xia, Y., & Xu, H. (2023) · International Journal on Semantic Web and Information Systems · doi:10.4018/ijswis.331082 · Cited by 8

Aggregating Local and Global Text Features for Linguistic Steganalysis

Xiang, L., Liu, Y., You, H., & Ou, C. (2022) · IEEE Signal Processing Letters · doi:10.1109/lsp.2022.3185946 · Cited by 10

A Text Classification Method Based on BERT-Att-TextCNN Model

Zhang, H., Shan, Y., Jiang, P., & Cai, X. (2022) · IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) · doi:10.1109/imcec55388.2022.10019808 · Cited by 8

TATA: Stance Detection via Topic-Agnostic and Topic-Aware Embeddings

Hanley, H. W. A., & Durumeric, Z. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.694 · Cited by 9

AHCL-TC: Adaptive Hypergraph Contrastive Learning Networks for Text Classification

Zhang, Z., Ni, H., Jia, X., Su, F., Liu, M., Yun, W., & Wu, G. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.127989 · Cited by 8

A hybrid re-fusion model for text classification

Liu, Q., Xiao, K., & Qian, Z. (2025) · Scientific Reports · doi:10.1038/s41598-025-90864-w · Cited by 7

Text Classification Using Deep Learning Methods

Zhang, C. (2022) · IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) · doi:10.1109/tocs56154.2022.10015956 · Cited by 7

Mal-Bert-GCN: Malware Detection by Combining Bert and GCN

Ding, Z., Xu, H., Guo, Y., Yan, L., Cui, L., & Hao, Z. (2022) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · doi:10.1109/trustcom56396.2022.00034 · Cited by 8

Graph learning and its advancements on large language models: A holistic survey

Wei, S., Wang, J., Zhao, Y., Chen, X., Hu, X., Li, Q., Zhuang, F., Ren, F., & Kou, G. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.132396 · Cited by 14

Classification of Research Papers on Radio Frequency Electromagnetic Field (RF-EMF) Using Graph Neural Networks (GNN)

Jang, Y., Won, K., Choi, H., & Shin, S. Y. (2023) · Applied Sciences · doi:10.3390/app13074614 · Cited by 7

scGraPhT: Merging Transformers and Graph Neural Networks for Single-Cell Annotation

Koç, E., Kulkul, E., Kaynar, G., Çukur, T., Açar, M., & Koç, A. (2025) · IEEE Transactions on Signal and Information Processing over Networks · doi:10.1109/tsipn.2025.3573591 · Cited by 7

Medical Graph Diffusion: Hybrid Graph Diffusion With Heterogeneous Graph Convolutional Networks for Medical Text Classification

Wang, G., Li, S., Liu, K., Hu, X., & Cao, C. (2025) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2025.3576247 · Cited by 7

A dynamic graph structural framework for implicit sentiment identification based on complementary semantic and structural information

Zhao, Y., Mamat, M., Aysa, A., & Ubul, K. (2024) · Scientific Reports · doi:10.1038/s41598-024-62269-8 · Cited by 6

DA-BAG: A multi-model fusion text classification method combining BERT and GCN using self-domain adversarial training

Shao, D., Su, S.-C., Ma, L., Yi, S., & Lai, H. (2024) · Journal of Intelligent Information Systems · doi:10.1007/s10844-024-00889-2 · Cited by 7

A parameter-free text classification method based on dual compressors

Mao, Y., Ding, Y., & Cui, T. (2025) · Knowledge and Information Systems · doi:10.1007/s10115-024-02335-9 · Cited by 8

An Intelligent system for the categorization of question time official documents of the Italian Chamber of Deputies

Cavalieri, A., Ducange, P., Fabi, S., Russo, F., & Tonellotto, N. (2022) · Journal of Information Technology & Politics · doi:10.1080/19331681.2022.2082622 · Cited by 7

DCAT: Combining Multisemantic Dual-Channel Attention Fusion for Text Classification

Dong, K., Liu, Y., Xu, F., & Liu, P. (2023) · IEEE Intelligent Systems · doi:10.1109/mis.2023.3268228 · Cited by 8

Knowledge Graph Completion with Triple Structure and Text Representation

Liu, S., Qin, Y., Xu, M., & Kolmanič, S. (2023) · International Journal of Computational Intelligence Systems · doi:10.1007/s44196-023-00271-0 · Cited by 6

DeFiTail: DeFi Protocol Inspection through Cross-Contract Execution Analysis

Li, W., Li, X., Zhang, Y., & Li, Z. (2024) · International World Wide Web Conference (WWW) · doi:10.1145/3589335.3651488 · Cited by 6

Learning label smoothing for text classification

Ren, H. Y., Zhao, Y., Zhang, Y., & Sun, W. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2005 · Cited by 8

GNN-encoder: Learning a Dual-encoder Architecture via Graph Neural Networks for Dense Passage Retrieval

Liu, J., Liu, J., Yang, Y., Wang, J., Wu, W., Zhao, D., & Yan, R. (2022) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2022.findings-emnlp.39 · Cited by 10

Text-RGNNs: Relational Modeling for Heterogeneous Text Graphs

Aras, A. C., Alikaşifoğlu, T., & Koç, A. (2024) · IEEE Signal Processing Letters · doi:10.1109/lsp.2024.3433568 · Cited by 5

Ladder-of-Thought: Using Knowledge as Steps to Elevate Stance Detection

Hu, K., Yan, M., Chong, W.-H., Yap, Y. K., Guan, C., Zhou, J. T., & Tsang, I. W.-H. (2024) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn60899.2024.10650428 · Cited by 6

Relationship extraction between entities with long distance dependencies and noise based on semantic and syntactic features

Wang, L., Wu, F. Q., Liu, X., Cao, J., Ma, M., & Qu, Z. (2025) · Scientific Reports · doi:10.1038/s41598-025-00915-5 · Cited by 8

Advancing minority stress detection with transformers: insights from the social media datasets

Chapagain, S., Cascalheira, C. J., Hamdi, S. M., Boubrahimi, S. F., & Scheer, J. R. (2025) · Social Network Analysis and Mining · doi:10.1007/s13278-025-01521-z · Cited by 7

Low-Resource Similar Case Matching in Legal Domain

Fang, J., Li, X., & Liu, Y. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-15931-2_47 · Cited by 5

Steno AI at SemEval-2023 Task 6: Rhetorical Role Labelling of Legal Documents using Transformers and Graph Neural Networks

Gupta, A., Furniturewala, S., Kumari, V., & Sharma, Y. (2023) · International Workshop on Semantic Evaluation (SemEval) · doi:10.18653/v1/2023.semeval-1.256 · Cited by 7

Chinese Address Recognition Method Based on Multi-Feature Fusion

Wang, Y., Wang, M., Ding, C., Yang, X., & Chen, J. (2022) · IEEE Access · doi:10.1109/access.2022.3213976 · Cited by 5

TTG-Text: A Graph-Based Text Representation Framework Enhanced by Typical Testors for Improved Classification

Sánchez-Antonio, C., Valdez-Rodríguez, J. E., & Calvo, H. (2024) · Mathematics · doi:10.3390/math12223576 · Cited by 4

LOGIC: LLM-originated guidance for internal cognitive improvement of small language models in stance detection

Lee, W., Lee, J., & Kim, H. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2585 · Cited by 4

Research on Natural Language Misleading Content Detection Method Based on Attention Mechanism

Liu, B. (2025) · IEEE Access · doi:10.1109/access.2025.3591455 · Cited by 5

BHGAttN: A Feature-Enhanced Hierarchical Graph Attention Network for Sentiment Analysis

Zhang, J., Cui, Z., Park, H. J., & Noh, G. (2022) · Entropy · doi:10.3390/e24111691 · Cited by 5

Attention is Not Always What You Need: Towards Efficient Classification of Domain-Specific Text

Wahba, Y., Madhavji, N., & Steinbacher, J. (2023) · arXiv.org · doi:10.1007/978-3-031-37963-5_80 · Cited by 4

SEDGCN: Sentiment Enhanced Dual Graph Convolutional Networks for Detecting Adverse Drug Reactions

Qiu, Y., Zhang, X., Wang, W., Wu, Y., Xu, B., Liu, H., & Lin, H. (2023) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm58861.2023.10385261 · Cited by 4

Multi-document influence on readers: augmenting social emotion prediction by learning document interactions

Mou, X., Peng, Q., Sun, Z., Bashir, M. F., & Li, H. (2024) · Neural Computing and Applications · doi:10.1007/s00521-024-09420-8 · Cited by 4

Dialectic Feature-Based Fuzzy Graph Learning for Label Propagation Assisting Text Classification

Madhu, C., & Sudhakar, M. (2024) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2024.3421595 · Cited by 4

Adapting GNNs for Document Understanding: A Flexible Framework With Multiview Global Graphs

Wu, Z. X., Zhang, Q., Miao, D., Zhao, X., & Shi, K. (2024) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2024.3468890 · Cited by 4

DynGraph-BERT: Combining BERT and GNN Using Dynamic Graphs for Inductive Semi-Supervised Text Classification

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