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Learning disentangled latent topics for Twitter rumour veracity classification
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Dougrez-Lewis, John, Liakata, Maria, Kochkina, Elena and He, Yulan (2021) Learning disentangled latent topics for Twitter rumour veracity classification. In: 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), Bangkok, Thailand, 1-6 Aug 2021. Published in: Proceedings of 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)
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Abstract
With the rapid growth of social media in the past decade, the news are no longer controlled by just a few mainstream sources. Users themselves create large numbers of potentially fictitious rumours, necessitating automated veracity classification systems. Here we present a novel approach towards automatically classifying rumours circulating on Twitter with respect to their veracity. We use a model built on Variational Autoencoder which disentangles the informational content of a tweet from the manner in which the information is written. This is achieved by obtaining latent topic vectors in an adversarial learning setting using the auxiliary task of stance classification. The latent vectors learnt in this way are used to predict rumour veracity, obtaining state-of-the-art accuracy scores on the PHEME dataset.
Item Type: | Conference Item (Paper) | ||||||||||||||||||
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Subjects: | H Social Sciences > HM Sociology P Language and Literature > P Philology. Linguistics Q Science > QA Mathematics Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||||||||||||||
Library of Congress Subject Headings (LCSH): | Twitter (Firm), Natural language processing (Computer science), Online social networks -- Data processing, Digital media, Computational linguistics , Speech processing systems , Semantic computing | ||||||||||||||||||
Journal or Publication Title: | Proceedings of 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) | ||||||||||||||||||
Official Date: | 2021 | ||||||||||||||||||
Dates: |
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Status: | Peer Reviewed | ||||||||||||||||||
Publication Status: | Published | ||||||||||||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||||||||||||
Date of first compliant deposit: | 20 July 2021 | ||||||||||||||||||
Date of first compliant Open Access: | 21 July 2021 | ||||||||||||||||||
RIOXX Funder/Project Grant: |
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Conference Paper Type: | Paper | ||||||||||||||||||
Title of Event: | 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) | ||||||||||||||||||
Type of Event: | Conference | ||||||||||||||||||
Location of Event: | Bangkok, Thailand | ||||||||||||||||||
Date(s) of Event: | 1-6 Aug 2021 | ||||||||||||||||||
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