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EventDNA : a dataset for Dutch news event extraction as a basis for news diversification

Camiel Colruyt, Orphée De Clercq (UGent) , Thierry Desot (UGent) and Veronique Hoste (UGent)
(2023) LANGUAGE RESOURCES AND EVALUATION. 57(1). p.189-221
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Abstract
News organizations increasingly tailor their news offering to the reader through personalized recommendation algorithms. However, automated recommendation algorithms reflect a commercial logic based on calculated relevance to the user, rather than aiming at a well-informed citizenry. In this paper, we introduce the EventDNA corpus, a dataset of 1773 Dutch-language news articles annotated with information on entities, news events and IPTC Media Topic codes, with the ultimate goal to outline a recommendation algorithm that uses news event diversity rather than previous reading behaviour as a key driver for personalized news recommendation. We describe the EventDNA annotation guidelines, which are inspired by the well-known ERE framework and conclude that it is not practical to apply a fixed event typology such as used in ERE to an unrestricted data context. The corpus and related source code is made available at haps://github.com/NewsDNA-LT3/.github.
Keywords
News recommendation, Event annotation, Event extraction

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Citation

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MLA
Colruyt, Camiel, et al. “EventDNA : A Dataset for Dutch News Event Extraction as a Basis for News Diversification.” LANGUAGE RESOURCES AND EVALUATION, vol. 57, no. 1, 2023, pp. 189–221, doi:10.1007/s10579-022-09623-2.
APA
Colruyt, C., De Clercq, O., Desot, T., & Hoste, V. (2023). EventDNA : a dataset for Dutch news event extraction as a basis for news diversification. LANGUAGE RESOURCES AND EVALUATION, 57(1), 189–221. https://doi.org/10.1007/s10579-022-09623-2
Chicago author-date
Colruyt, Camiel, Orphée De Clercq, Thierry Desot, and Veronique Hoste. 2023. “EventDNA : A Dataset for Dutch News Event Extraction as a Basis for News Diversification.” LANGUAGE RESOURCES AND EVALUATION 57 (1): 189–221. https://doi.org/10.1007/s10579-022-09623-2.
Chicago author-date (all authors)
Colruyt, Camiel, Orphée De Clercq, Thierry Desot, and Veronique Hoste. 2023. “EventDNA : A Dataset for Dutch News Event Extraction as a Basis for News Diversification.” LANGUAGE RESOURCES AND EVALUATION 57 (1): 189–221. doi:10.1007/s10579-022-09623-2.
Vancouver
1.
Colruyt C, De Clercq O, Desot T, Hoste V. EventDNA : a dataset for Dutch news event extraction as a basis for news diversification. LANGUAGE RESOURCES AND EVALUATION. 2023;57(1):189–221.
IEEE
[1]
C. Colruyt, O. De Clercq, T. Desot, and V. Hoste, “EventDNA : a dataset for Dutch news event extraction as a basis for news diversification,” LANGUAGE RESOURCES AND EVALUATION, vol. 57, no. 1, pp. 189–221, 2023.
@article{01GK18R97NGS8S3XM5CYZ3K3TJ,
  abstract     = {{News organizations increasingly tailor their news offering to the reader through personalized recommendation algorithms. However, automated recommendation algorithms reflect a commercial logic based on calculated relevance to the user, rather than aiming at a well-informed citizenry. In this paper, we introduce the EventDNA corpus, a dataset of 1773 Dutch-language news articles annotated with information on entities, news events and IPTC Media Topic codes, with the ultimate goal to outline a recommendation algorithm that uses news event diversity rather than previous reading behaviour as a key driver for personalized news recommendation. We describe the EventDNA annotation guidelines, which are inspired by the well-known ERE framework and conclude that it is not practical to apply a fixed event typology such as used in ERE to an unrestricted data context. The corpus and related source code is made available at haps://github.com/NewsDNA-LT3/.github.}},
  author       = {{Colruyt, Camiel and De Clercq, Orphée and Desot, Thierry and Hoste, Veronique}},
  issn         = {{1574-020X}},
  journal      = {{LANGUAGE RESOURCES AND EVALUATION}},
  keywords     = {{News recommendation,Event annotation,Event extraction}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{189--221}},
  title        = {{EventDNA : a dataset for Dutch news event extraction as a basis for news diversification}},
  url          = {{http://doi.org/10.1007/s10579-022-09623-2}},
  volume       = {{57}},
  year         = {{2023}},
}
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