mlsanityData to 7 Oct 2026

Transformer based Automatic COVID-19 Fake News Detection System

arXiv 2101.00180 ↗First posted 1 Jan 2021cs.CLcited by 14

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Abstract (arXiv)

Recent rapid technological advancements in online social networks such as Twitter have led to a great incline in spreading false information and fake news. Misinformation is especially prevalent in the ongoing coronavirus disease (COVID-19) pandemic, leading to individuals accepting bogus and potentially deleterious claims and articles. Quick detection of fake news can reduce the spread of panic and confusion among the public. For our analysis in this paper, we report a methodology to analyze the reliability of information shared on social media pertaining to the COVID-19 pandemic. Our best approach is based on an ensemble of three transformer models (BERT, ALBERT, and XLNET) to detecting fake news. This model was trained and evaluated in the context of the ConstraintAI 2021 shared task COVID19 Fake News Detection in English. Our system obtained 0.9855 f1-score on testset and ranked 5th among 160 teams.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 15 of its 34 references that are in the map. First posted on arXiv 1 Jan 2021.

Builds on

15 of 34 references.

References · 15

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2019XLNet: Generalized Autoregressive Pretraining for Language Understandingcited by 2,801
  4. 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,772
  5. 2019Transformer-XL: Attentive Language Models Beyond a Fixed-Length Contextcited by 1,830
  6. 2016Enriching Word Vectors with Subword Informationcited by 1,578
  7. 2018Automated Fact Checking: Task formulations, methods and future directionscited by 96
  8. 2020CoAID: COVID-19 Healthcare Misinformation Datasetcited by 83
  9. 2020Fighting an Infodemic: COVID-19 Fake News Datasetcited by 82
  10. 2020FakeCovid -- A Multilingual Cross-domain Fact Check News Dataset for COVID-19cited by 60
  11. 2020ReCOVery: A Multimodal Repository for COVID-19 News Credibility Researchcited by 44
  12. 2020MM-COVID: A Multilingual and Multimodal Data Repository for Combating COVID-19 Disinformationcited by 36
3 more
  1. 2020Characterizing COVID-19 Misinformation Communities Using a Novel Twitter Datasetcited by 32
  2. 2020Two Stage Transformer Model for COVID-19 Fake News Detection and Fact Checkingcited by 15
  3. 2019A Benchmark Study of Machine Learning Models for Online Fake News Detectioncited by 6

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Cited by year (2026 to 7 Oct)

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

14 papers.

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  1. 2023Adapting Fake News Detection to the Era of Large Language Modelscited by 14
  2. 2022Combating Health Misinformation in Social Media: Characterization, Detection, Intervention, and Open Issuescited by 6
  3. 2025Semantic and Contextual Modeling for Malicious Comment Detection with BERT-BiLSTMcited by 5
  4. 2025Applying Text Mining to Analyze Human Question Asking in Creativity Researchcited by 3
  5. 2022A Comparative Study on COVID-19 Fake News Detection Using Different Transformer Based Modelscited by 2
  6. 2022Multiverse: Multilingual Evidence for Fake News Detectioncited by 2
  7. 2023How Good Are SOTA Fake News Detectorscited by 2
  8. 2021Checkovid: A COVID-19 misinformation detection system on Twitter using network and content mining perspectivescited by 1
  9. 2021Case Study on Detecting COVID-19 Health-Related Misinformation in Social Mediacited by 0
  10. 2021COVID-19 Fake News Detection Using Bidirectional Encoder Representations from Transformers Based Modelscited by 0
  11. 2023Bengali Fake Reviews: A Benchmark Dataset and Detection Systemcited by 0
  12. 2024Health Misinformation in Social Networks: A Survey of IT Approachescited by 0
2 more
  1. 2024FNDEX: Fake News and Doxxing Detection with Explainable AIcited by 0
  2. 2026An Evidence-Grounded Retrieval-Augmented Transformer Framework for Health Misinformation Verificationcited by 0