mlsanityData to 7 Oct 2026

Cross-SEAN: A Cross-Stitch Semi-Supervised Neural Attention Model for COVID-19 Fake News Detection

arXiv 2102.08924 ↗First posted 17 Feb 2021cs.CL cs.LGcited by 15

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Abstract (arXiv)

As the COVID-19 pandemic sweeps across the world, it has been accompanied by a tsunami of fake news and misinformation on social media. At the time when reliable information is vital for public health and safety, COVID-19 related fake news has been spreading even faster than the facts. During times such as the COVID-19 pandemic, fake news can not only cause intellectual confusion but can also place lives of people at risk. This calls for an immediate need to contain the spread of such misinformation on social media. We introduce CTF, the first COVID-19 Twitter fake news dataset with labeled genuine and fake tweets. Additionally, we propose Cross-SEAN, a cross-stitch based semi-supervised end-to-end neural attention model, which leverages the large amount of unlabelled data. Cross-SEAN partially generalises to emerging fake news as it learns from relevant external knowledge. We compare Cross-SEAN with seven state-of-the-art fake news detection methods. We observe that it achieves 0.95 F1 Score on CTF, outperforming the best baseline by 9%. We also develop Chrome-SEAN, a Cross-SEAN based chrome extension for real-time detection of fake tweets.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 24 of its 79 references that are in the map. First posted on arXiv 17 Feb 2021.

Builds on

24 of 79 references.

References · 24

  1. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  2. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  3. 2017mixup: Beyond Empirical Risk Minimizationcited by 5,155
  4. 2015A large annotated corpus for learning natural language inferencecited by 1,837
  5. 2019Unsupervised Data Augmentation for Consistency Trainingcited by 1,057
  6. 2017Fake News Detection on Social Media: A Data Mining Perspectivecited by 334
  7. 2016Adversarial Training Methods for Semi-Supervised Text Classificationcited by 280
  8. 2015Semi-supervised Sequence Learningcited by 198
  9. 2020MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classificationcited by 186
  10. 2019Fake News Detection on Social Media using Geometric Deep Learningcited by 115
  11. 2017CSI: A Hybrid Deep Model for Fake News Detectioncited by 101
  12. 2020Fighting an Infodemic: COVID-19 Fake News Datasetcited by 82
12 more
  1. 2019Variational Pretraining for Semi-supervised Text Classificationcited by 41
  2. 2020Hostility Detection Dataset in Hindicited by 31
  3. 2017Call Attention to Rumors: Deep Attention Based Recurrent Neural Networks for Early Rumor Detectioncited by 25
  4. 2020Revisiting LSTM Networks for Semi-Supervised Text Classification via Mixed Objective Functioncited by 23
  5. 2020Hate is the New Infodemic: A Topic-aware Modeling of Hate Speech Diffusion on Twittercited by 16
  6. 2020GeoCoV19: A Dataset of Hundreds of Millions of Multilingual COVID-19 Tweets with Location Informationcited by 15
  7. 2018Semi-supervised Content-based Detection of Misinformation via Tensor Embeddingscited by 14
  8. 2014TweetCred: Real-Time Credibility Assessment of Content on Twittercited by 12
  9. 2019Variational Sequential Labelers for Semi-Supervised Learningcited by 11
  10. 2020Two-path Deep Semi-supervised Learning for Timely Fake News Detectioncited by 9
  11. 2020Prevalence of Low-Credibility Information on Twitter During the COVID-19 Outbreakcited by 6
  12. 2019Multitask Learning for Blackmarket Tweet Detectioncited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 3; 2023: 2; 2024: 3; 2025: 3; 2026: 1.

15 papers.

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  1. 2021A Survey on Multimodal Disinformation Detectioncited by 47
  2. 2025PCoT: Persuasion-Augmented Chain of Thought for Detecting Fake News and Social Media Disinformationcited by 11
  3. 2024A Semi-supervised Fake News Detection using Sentiment Encoding and LSTM with Self-Attentioncited by 8
  4. 2021Combining exogenous and endogenous signals with a semi-supervised co-attention network for early detection of COVID-19 fake tweetscited by 5
  5. 2022The use of Data Augmentation as a technique for improving neural network accuracy in detecting fake news about COVID-19cited by 3
  6. 2022A Comparative Study on COVID-19 Fake News Detection Using Different Transformer Based Modelscited by 2
  7. 2024LOSS-GAT: Label Propagation and One-Class Semi-Supervised Graph Attention Network for Fake News Detectioncited by 2
  8. 2021Checkovid: A COVID-19 misinformation detection system on Twitter using network and content mining perspectivescited by 1
  9. 2022Machine Learning-based Automatic Annotation and Detection of COVID-19 Fake Newscited by 1
  10. 2024Empowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media postscited by 1
  11. 2025FakeZero: Real-Time, Privacy-Preserving Misinformation Detection for Facebook and Xcited by 1
  12. 2023A Meta Path-based Approach for Rumor Detection on Social Mediacited by 0
3 more
  1. 2023A Comparative Analysis of the COVID-19 Infodemic in English and Chinese: Insights from Social Media Textual Datacited by 0
  2. 2025CrediBench: Building Web-Scale Network Datasets for Information Integritycited by 0
  3. 2026ExTax: Explainable Disinformation Detection via Persuasion, Emotion, and Narrative Role Taxonomiescited by 0