Domain Adaptive Fake News Detection via Reinforcement Learning

Author:

Mosallanezhad Ahmadreza1,Karami Mansooreh1,Shu Kai2,Mancenido Michelle V.1,Liu Huan1

Affiliation:

1. Arizona State University, USA

2. Illinois Institute of Technology, USA

Funder

NSF (National Science Foundation)

U.S. Department of Homeland Security

ONR

Publisher

ACM

Reference47 articles.

1. Shai Ben-David , John Blitzer , Koby Crammer , Alex Kulesza , Fernando Pereira , and Jennifer Wortman Vaughan . 2010. A theory of learning from different domains. Machine learning 79, 1-2 ( 2010 ), 151–175. Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, and Jennifer Wortman Vaughan. 2010. A theory of learning from different domains. Machine learning 79, 1-2 (2010), 151–175.

2. Published by Statista Research Departmentand Sep 7. 2021. Daily social media usage worldwide. https://www.statista.com/statistics/433871/daily-social-media-usage-worldwide/ Published by Statista Research Departmentand Sep 7. 2021. Daily social media usage worldwide. https://www.statista.com/statistics/433871/daily-social-media-usage-worldwide/

3. Mitigating Bias in Session-based Cyberbullying Detection: A Non-Compromising Approach

4. Junyoung Chung Caglar Gulcehre KyungHyun Cho and Yoshua Bengio. 2014. Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555(2014). Junyoung Chung Caglar Gulcehre KyungHyun Cho and Yoshua Bengio. 2014. Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555(2014).

5. Alistair Coleman. 2020. ’hundreds dead’ because of covid-19 misinformation. https://www.bbc.com/news/world-53755067 Alistair Coleman. 2020. ’hundreds dead’ because of covid-19 misinformation. https://www.bbc.com/news/world-53755067

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