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Deep Fake Recognition in Tweets Using Text Augmentation, Word Embeddings and Deep Learning

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Computational Science and Its Applications – ICCSA 2021 (ICCSA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12954))

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Abstract

Spreading of automatically generated clickbaits, fake news, and fake reviews undermines the veracity of the internet as a credible source of information. We investigate the problem of recognizing automatically generated short texts by exploring different Deep Learning models. To improve the classification results, we use text augmentation techniques and classifier hyperparameter optimization. For word embedding and vectorization we use Glove and RoBERTa. We compare the performance of dense neural network, convolutional neural network, gated recurrent network, and hierarchical attention network. The experiments on the TweepFake dataset achieved an 89.7% accuracy.

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Acknowledgment

Future work will aim on the improvement of discussed architectures specifically focusing on the problem of the small dataset.

Author information

Authors and Affiliations

  1. Kaunas University of Technology, 51368, Kaunas, Lithuania

    Senait G. Tesfagergish & Robertas Damaševičius

  2. Vytautas Magnus University, 44404, Kaunas, Lithuania

    Jurgita Kapočiūtė-Dzikienė

Authors
  1. Senait G. Tesfagergish
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  2. Robertas Damaševičius
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  3. Jurgita Kapočiūtė-Dzikienė
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Corresponding author

Correspondence to Robertas Damaševičius .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Monash University, Clayton, VIC, Australia

    David Taniar

  7. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

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Tesfagergish, S.G., Damaševičius, R., Kapočiūtė-Dzikienė, J. (2021). Deep Fake Recognition in Tweets Using Text Augmentation, Word Embeddings and Deep Learning. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12954. Springer, Cham. https://doi.org/10.1007/978-3-030-86979-3_37

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  • DOI: https://doi.org/10.1007/978-3-030-86979-3_37

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