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Cited by 5Linguistics and Discourse AnalysisSentiment Analysis and Opinion MiningSpeech and dialogue systems

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QT30: A Corpus of Argument and Conflict in Broadcast Debate

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Hautli-Janisz, Annette, Kikteva, Zlata, Siskou, Wassiliki, Gorska, Kamila, Becker, Ray, Reed, Chris·2022·Proceedings of the Language Resources and Evaluation Conference
DOI 10.63317/4n6ua5xrt9p8
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Abstract

Broadcast political debate is a core pillar of democracy: it is the public's easiest access to opinions that shape policies and enables the general public to make informed choices.With QT30, we present the largest corpus of analysed dialogical argumentation ever created (19,842 utterances, 280,000 words) and also the largest corpus of analysed broadcast political debate to date, using 30 episodes of BBC's 'Question Time' from 2020 and 2021.Question Time is the prime institution in UK broadcast political debate and features questions from the public on current political issues, which are responded to by a weekly panel of five figures of UK politics and society.QT30 is highly argumentative and combines language of well-versed political rhetoric with direct, often combative, justification-seeking of the general public.QT30 is annotated with Inference Anchoring Theory, a framework well-known in argument mining, which encodes the way arguments and conflicts are created and reacted to in dialogical settings.The resource is freely available at http://corpora.aifdb.org/qt30.

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Research works printed but not linked: 23

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Metadata

Authors
Hautli-Janisz, A., Kikteva, Z., Siskou, W., Gorska, K., Becker, R., & Reed, C.
Affiliations
  • University of Passau (DE)
  • University of Dundee (GB)
ORCID
Venue
Proceedings of the Language Resources and Evaluation Conference
Publisher
European Language Resources Association (ELRA)
Published
2022-06
Pages
3291-3300
ISSN
2522-2686
DOI
10.63317/4n6ua5xrt9p8
OpenAlex
W7160236294
Cited by
5
References
0
Citations by year
2026: 5
FWCI
0.00
Type
conference paper
Language
en
Open access
Licence
cc-by-nc
Locations
  • Language Resources and Evaluation Conference (LREC) (publishedVersion, cc-by-nc)
  • Discovery Research Portal (University of Dundee) (submittedVersion, cc-by-nc)
  • KOPS (University of Konstanz) (submittedVersion)
Topics
  • Social Sciences › Linguistics and Language › Linguistics and Discourse Analysis
  • Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
  • Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
Keywords
dialogic argumentation, argument mining, question time, BBC, political rhetoric, annotated corpus

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CoChat. (2026). Citation check: QT30: A Corpus of Argument and Conflict in Broadcast Debate. https://app.cochat.ai/papers/10.63317/4n6ua5xrt9p8
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Hautli-Janisz, A., Kikteva, Z., Siskou, W., Gorska, K., Becker, R., & Reed, C. (2022). QT30: A Corpus of Argument and Conflict in Broadcast Debate. Proceedings of the Language Resources and Evaluation Conference. https://doi.org/10.63317/4n6ua5xrt9p8