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Journal article

A semi-supervised approach to message stance classification

Abstract:

Social media communications are becoming increasingly prevalent; some useful, some false, whether unwittingly or maliciously. An increasing number of rumours daily flood the social networks. Determining their veracity in an autonomous way is a very active and challenging field of research, with a variety of methods proposed. However, most of the models rely on determining the constituent messages' stance towards the rumour, a feature known as the "wisdom of the crowd". Although several superv...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/TKDE.2018.2880192

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
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Name:
UK Defence Science and Technology Laboratory
Grant:
DSTLX-1000107083
Publisher:
IEEE
Journal:
IEEE Transactions on Knowledge and Data Engineering More from this journal
Volume:
31
Issue:
1
Pages:
1 - 11
Publication date:
2018-11-09
Acceptance date:
2018-11-01
DOI:
EISSN:
1558-2191
ISSN:
1041-4347
Language:
English
Keywords:
Pubs id:
pubs:938147
UUID:
uuid:06f3df1b-73f5-42bc-bf16-1b593763ba4e
Local pid:
pubs:938147
Source identifiers:
938147
Deposit date:
2018-11-05

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