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MeVer team tackling Corona virus and 5G conspiracy using ensemble classification based on BERT

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MeVer team tackling Corona virus and 5G conspiracy using ensemble classification based on BERT

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Presentation of the approach developed for the task of 'FakeNews: Corona virus and 5G conspiracy' at the MediaEval 2020 benchmark.

Presentation of the approach developed for the task of 'FakeNews: Corona virus and 5G conspiracy' at the MediaEval 2020 benchmark.

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MeVer team tackling Corona virus and 5G conspiracy using ensemble classification based on BERT

  1. 1. MeVer team tackling Corona virus and 5G conspiracy using ensemble classification based on BERT Olga Papadopoulou Giorgos Kordopatis-Zilos Symeon Papadopoulos FakeNews: Corona virus and 5G conspiracy
  2. 2. Motivation • Imbalanced and relatively small dataset • 5G-Conspiracy: 1,335 • Other-Conspiracy: 712 • No-Conspiracy: 4,198 • Sub-sample majority classes • Ensemble learning of multiple classification networks • Two-stage classification approach
  3. 3. Proposed Approach CL2 CL1 CLN 5G and other conspiracy samples No conspiracy Random sampling Step 1 Step 2 Majority vote Final Predictions CLf1 CLf2 No conspiracy detections Conspiracy detections CLf1 = CLf2 = 1 1: 5G Conspiracy 2: Other conspiracy 3: Non-Conspiracy 1: 5G Conspiracy 2: Other conspiracy Yes No 5G Other All samples ... Σ(C𝐿i) > 𝑁 2 Yes No 1: Conspiracy 0: Non-conspiracy • Sub-sample Non-conspiracy class • Binary classification • Majority voting
  4. 4. Results Method MCC Three-class BERT 0,42 Proposed approach 0,81 Our proposed approach achieved a score of 0.413 in terms of MCC on the provided testing set of unseen tweets.
  5. 5. Thank you for your attention! With the support of: Get in touch: Olga Papadopoulou: olgapapa@iti.gr / @olgpapa MeVer team: https://mever.iti.gr/web/ / @meverteam / Questions ? /

Editor's Notes

  • Thank you very much for your attention. If you have any questions or comments, please don't hesitate to contact me or our team via email or through Twitter. Also, you may find code in GitHub for the evaluation and reproduction of the experimental results. Thank you.

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