Reinforcement Learning-based Counter-Misinformation Response Generation: A Case Study of COVID-19 Vaccine Misinformation-Reference-Cited by-同舟云学术

Reinforcement Learning-based Counter-Misinformation Response Generation: A Case Study of COVID-19 Vaccine Misinformation

Published:2023-04-30 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM Web Conference 2023
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Author:

He Bing¹^ORCID,Ahamad Mustaque¹^ORCID,Kumar Srijan¹^ORCID

Affiliation:

1. Georgia Institute of Technology, USA

Funder

NSF (National Science Foundation)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3543507.3583388

Reference121 articles.

1. Widespread Misinformation About Infertility Continues to Create COVID-19 Vaccine Hesitancy

2. GraphNLI: A Graph-based Natural Language Inference Model for Polarity Prediction in Online Debates

3. Jennifer Allen , Antonio A. Arechar , Gordon Pennycook , and David G. Rand . 2021. Scaling up fact-checking using the wisdom of crowds. Science Advances 7 (9 2021 ). Issue 36. https://doi.org/10.1126/sciadv.abf4393 10.1126/sciadv.abf4393 Jennifer Allen, Antonio A. Arechar, Gordon Pennycook, and David G. Rand. 2021. Scaling up fact-checking using the wisdom of crowds. Science Advances 7 (9 2021). Issue 36. https://doi.org/10.1126/sciadv.abf4393

4. Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in Twitter’s Birdwatch crowdsourced fact-checking program

5. Counter-Argument Generation by Attacking Weak Premises

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