Applications of machine learning for COVID-19 misinformation: a systematic review-Reference-Cited by-同舟云学术

Applications of machine learning for COVID-19 misinformation: a systematic review

Published:2022-07-29 Issue:1 Volume:12 Page:
ISSN:1869-5450
Container-title:Social Network Analysis and Mining
language:en
Short-container-title:Soc. Netw. Anal. Min.

Author:

Sanaullah A. R.,Das Anupam,Das Anik^ORCID,Kabir Muhammad Ashad,Shu Kai

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Human-Computer Interaction,Media Technology,Communication,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s13278-022-00921-9.pdf

Reference125 articles.

1. Ahinkorah BO, Ameyaw EK, Hagan JE et al (2020) Rising above misinformation or fake news in Africa: another strategy to control COVID-19 spread. Front Commun 5:45. https://doi.org/10.3389/fcomm.2020.00045

2. Akon S, Bhuiyan A (2020) COVID-19: Rumors and Youth Vulnerabilities in Bangladesh

3. Al-Rakhami M, Al-Amri A (2020) Lies Kill, facts save: detecting COVID-19 misinformation in Twitter. IEEE Access 8:155961–155970. https://doi.org/10.1109/ACCESS.2020.3019600

4. Alam F, Dalvi F, Shaar Set al (2021) Fighting the covid-19 infodemic in social media: a holistic perspective and a call to arms. In: ICWSM

5. Alkhalifa R, Yoong T, Kochkina Eet al (2020) QMUL-SDS at CheckThat! 2020: determining COVID-19 tweet check-worthiness using an enhanced CT-BERT with numeric expressions. arXiv:2008.13160

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