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    <abstract>The 3C Citation Context Classification task is the first shared task addressing citation context classification. The two subtasks, A and B, associated with this shared task, involves the classification of citations based on their purpose and influence, respectively. Both tasks use a portion of the new ACT dataset, developed by the researchers at The Open University, UK. The tasks were hosted on Kaggle, and the participated systems were evaluated using the macro f-score. Three teams participated in subtask A and four teams participated in subtask B. The best performing systems obtained an overall score of 0.2056 for subtask A and 0.5556 for subtask B, outperforming the simple majority class baseline models, which scored 0.11489 and 0.32249, respectively. In this paper we provide a report specifying the shared task, the dataset used, a short description of the participating systems and the final results obtained by the teams based on the evaluation criteria. The shared task has been organised as part of the 8th International Workshop on Mining Scientific Publications (WOSP 2020) workshop.</abstract>
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%0 Conference Proceedings
%T Overview of the 2020 WOSP 3C Citation Context Classification Task
%A Kunnath, Suchetha Nambanoor
%A Pride, David
%A Gyawali, Bikash
%A Knoth, Petr
%Y Knoth, Petr
%Y Stahl, Christopher
%Y Gyawali, Bikash
%Y Pride, David
%Y Kunnath, Suchetha N.
%Y Herrmannova, Drahomira
%S Proceedings of the 8th International Workshop on Mining Scientific Publications
%D 2020
%8 05 aug
%I Association for Computational Linguistics
%C Wuhan, China
%F kunnath-etal-2020-overview
%X The 3C Citation Context Classification task is the first shared task addressing citation context classification. The two subtasks, A and B, associated with this shared task, involves the classification of citations based on their purpose and influence, respectively. Both tasks use a portion of the new ACT dataset, developed by the researchers at The Open University, UK. The tasks were hosted on Kaggle, and the participated systems were evaluated using the macro f-score. Three teams participated in subtask A and four teams participated in subtask B. The best performing systems obtained an overall score of 0.2056 for subtask A and 0.5556 for subtask B, outperforming the simple majority class baseline models, which scored 0.11489 and 0.32249, respectively. In this paper we provide a report specifying the shared task, the dataset used, a short description of the participating systems and the final results obtained by the teams based on the evaluation criteria. The shared task has been organised as part of the 8th International Workshop on Mining Scientific Publications (WOSP 2020) workshop.
%U https://aclanthology.org/2020.wosp-1.12
%P 75-83

Markdown (Informal)

[Overview of the 2020 WOSP 3C Citation Context Classification Task](https://aclanthology.org/2020.wosp-1.12) (Kunnath et al., WOSP 2020)

• Overview of the 2020 WOSP 3C Citation Context Classification Task (Kunnath et al., WOSP 2020)

ACL

• Suchetha Nambanoor Kunnath, David Pride, Bikash Gyawali, and Petr Knoth. 2020. Overview of the 2020 WOSP 3C Citation Context Classification Task. In Proceedings of the 8th International Workshop on Mining Scientific Publications, pages 75–83, Wuhan, China. Association for Computational Linguistics.