| Detecting rumors from microblogs with recurrent neural networks J Ma, W Gao, P Mitra, S Kwon, BJ Jansen, KF Wong, M Cha AAAI Press, 2016 | 756 | 2016 |
| Detect rumors using time series of social context information on microblogging websites J Ma, W Gao, Z Wei, Y Lu, KF Wong Proceedings of the 24th ACM international on conference on information and …, 2015 | 453 | 2015 |
| Detect rumors in microblog posts using propagation structure via kernel learning J Ma, W Gao, KF Wong Association for Computational Linguistics, 2017 | 328 | 2017 |
| Rumor detection on twitter with tree-structured recursive neural networks J Ma, W Gao, KF Wong Association for Computational Linguistics, 2018 | 296 | 2018 |
| Detect rumor and stance jointly by neural multi-task learning J Ma, W Gao, KF Wong Companion proceedings of the the web conference 2018, 585-593, 2018 | 150 | 2018 |
| Detect Rumors on Twitter by Promoting Information Campaigns with Generative Adversarial Learning J Ma, W Gao, KF Wong WWW2019, 2019 | 111 | 2019 |
| From retweet to believability: Utilizing trust to identify rumor spreaders on twitter B Rath, W Gao, J Ma, J Srivastava Proceedings of the 2017 IEEE/ACM International Conference on Advances in …, 2017 | 66 | 2017 |
| Sentence-level evidence embedding for claim verification with hierarchical attention networks J Ma, W Gao, S Joty, KF Wong Association for Computational Linguistics, 2019 | 51 | 2019 |
| An attention-based rumor detection model with tree-structured recursive neural networks J Ma, W Gao, S Joty, KF Wong ACM Transactions on Intelligent Systems and Technology (TIST) 11 (4), 1-28, 2020 | 21 | 2020 |
| Discovering attractive segments in the user-generated video streams Z Wang, J Zhou, J Ma, J Li, J Ai, Y Yang Information Processing & Management 57 (1), 102130, 2020 | 19 | 2020 |
| Debunking rumors on Twitter with tree transformer J Ma, W Gao ACL, 2020 | 12 | 2020 |
| Utilizing computational trust to identify rumor spreaders on Twitter B Rath, W Gao, J Ma, J Srivastava Social Network Analysis and Mining 8 (1), 1-16, 2018 | 11 | 2018 |
| guided Helpful Answer Identification in E-commerce W Zhang, W Lam, Y Deng, J Ma Proceedings of The Web Conference 2020, 2620-2626, 2020 | 10 | 2020 |
| Attention-based multi-level feature fusion for named entity recognition Z Yang, H Chen, J Zhang, J Ma, Y Chang International Joint Conference on Artificial Intelligence, 2020 | 9 | 2020 |
| AnswerFact: Fact checking in product question answering W Zhang, Y Deng, J Ma, W Lam Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 6 | 2020 |
| Rumor Detection on Twitter with Claim-Guided Hierarchical Graph Attention Networks H Lin, J Ma, M Cheng, Z Yang, L Chen, G Chen arXiv preprint arXiv:2110.04522, 2021 | 5 | 2021 |
| Cross-lingual COVID-19 Fake News Detection J Du, Y Dou, C Xia, L Cui, J Ma, SY Philip 2021 International Conference on Data Mining Workshops (ICDMW), 859-862, 2021 | 2 | 2021 |
| UIR-PKU: Twitter-OpinMiner System for Sentiment Analysis in Twitter at SemEval 2015 X Han, B Li, J Ma, Y Zhang, G Ou, T Wang, K Wong Proceedings of the 9th International Workshop on Semantic Evaluation …, 2015 | 2 | 2015 |
| Exploring nonnegative and low-rank correlation for noise-resistant spectral clustering Z Wang, L Zuo, J Ma, S Chen, J Li, Z Kang, L Zhang World Wide Web 23 (3), 2107-2127, 2020 | 1 | 2020 |
| DecBERT: Enhancing the Language Understanding of BERT with Causal Attention Masks Z Luo, Y Xi, J Ma, Z Yang, X Mao, C Fan, R Zhang arXiv preprint arXiv:2204.08688, 2022 | | 2022 |
Wei GaoSingapore Management University在 smu.edu.sg 的电子邮件经过验证
