Speech acts in the Dutch COVID-19 Press Conferences

Abstract An open source corpus of all Dutch COVID-19 Press Conferences with sentences annotated on the basis of John Searle’s Speech Act taxonomy was created. It contains all 58 press conferences held between March 6 2020 and April 20 2021 and has 9.441 manually annotated sentences. Speech acts were annotated in a consistent manner, with a Krippendorff’s alpha of .71. The corpus is easy to use and rich in metadata, with lexical, syntactic, discourse (speaker, question or answer) features and information on the type of regulations being present. We analyse the press conferences in terms of spee... Mehr ...

Verfasser: Schueler, Daan
Marx, Maarten
Dokumenttyp: Artikel
Erscheinungsdatum: 2022
Reihe/Periodikum: Language Resources and Evaluation ; volume 57, issue 2, page 869-892 ; ISSN 1574-020X 1574-0218
Verlag/Hrsg.: Springer Science and Business Media LLC
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27457047
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : http://dx.doi.org/10.1007/s10579-022-09602-7

Abstract An open source corpus of all Dutch COVID-19 Press Conferences with sentences annotated on the basis of John Searle’s Speech Act taxonomy was created. It contains all 58 press conferences held between March 6 2020 and April 20 2021 and has 9.441 manually annotated sentences. Speech acts were annotated in a consistent manner, with a Krippendorff’s alpha of .71. The corpus is easy to use and rich in metadata, with lexical, syntactic, discourse (speaker, question or answer) features and information on the type of regulations being present. We analyse the press conferences in terms of speech act usage, giving insight into the use of speech acts over time, the relation of speech act usage to real world phenomena, the general structure of the press conferences and the division of roles between speakers. Relations were found between speech act usage and the type of press conference (i.e. easing, tightening or neutral) as well as the number of hospital admissions. Speech act classes showed preferred locations within the press conferences, indicating a general structure. Distinct roles between speakers were identified. We also investigate the use of our set of labelled sentences for training a speech act classifier and achieve a reasonable accuracy of .73 and a mean reciprocal rank of .74 with the state of the art transformer RoBERTa model.