Data augmentation for rumor detection using context-sensitive neural language model with large-scale credibility corpus

Han, S., Gao, J. orcid.org/0000-0002-3610-8748 and Ciravegna, F. orcid.org/0000-0001-5817-4810 (2019) Data augmentation for rumor detection using context-sensitive neural language model with large-scale credibility corpus. In: Learning from Limited Labeled Data: ICLR 2019 Workshop. Seventh International Conference on Learning Representations, 06-09 May 2019, New Orleans, Louisiana, United States. OpenReview .

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2019 The Authors.
Keywords: Rumor Detection; Data Augmentation; Social Media; Neural Language Models; Weak Supervision
Dates:
  • Accepted: 17 April 2019
  • Published (online): 6 May 2019
  • Published: 6 May 2019
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 10 May 2019 11:14
Last Modified: 15 Jul 2020 12:35
Published Version: https://openreview.net/forum?id=SyxCysRNdV
Status: Published
Publisher: OpenReview
Refereed: Yes
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