Disinformation Detection: Knowledge Infusion with Transfer Learning and Visualizations-Reference-Cited by-同舟云学术

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Disinformation Detection: Knowledge Infusion with Transfer Learning and Visualizations

Published:2023 Issue: Volume: Page:468-475
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Schütz Mina^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-28241-6_54

Reference56 articles.

1. Aggarwal, A., Chauhan, A., Kumar, D., Mittal, M., Verma, S.: Classification of fake news by fine-tuning deep bidirectional transformers based language model. EAI Endorsed Trans. Scalable Inf. Syst. Online First (2020). https://doi.org/10.4108/eai.13-7-2018.163973

2. Lecture Notes in Computer Science;H Ahmed,2017

3. Ahmed, H., Traoré, I., Saad, S.: Detecting opinion spams and fake news using text classification. Secur. Priv. 1 (2018)

4. Ajao, O., Bhowmik, D., Zargari, S.: Sentiment aware fake news detection on online social networks. In: ICASSP 2019–2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2507–2511 (2019)

5. Al-Ash, H.S., Wibowo, W.C.: Fake news identification characteristics using named entity recognition and phrase detection. In: 2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE), pp. 12–17 (2018)

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