Due to unprecedented events following the global pandemic situation, this year, the 8th International Workshop on Mining Scientific Publications (WOSP), 2020 was fully organised virtually. The entire workshop constituted a single day, with four sessions, featuring keynote talks, with accepted paper presentations and a shared task on citation context classification. More details regarding the program structure can be found here. The workshop this year was organised by CORE, The Open University, UK, in collaboration with Oak Ridge National Laboratory (ORNL), Tennessee, US. More about it here.
Researchers from CORE are organizing a new shared task: the ‘3C’ Citation Context Classification Task, as part of the International Workshop on Mining Scientific Publications, WOSP 2020 (https://wosp.core.ac.uk/jcdl2020/index.html). The new task will be hosted on Kaggle (https://www.kaggle.com/c/about/inclass), which is a popular Machine Learning/Data Science competition hosting platform. The competition uses a portion of the Academic Citation Typing (ACT) dataset (http://oro.open.ac.uk/60670/), which is the largest dataset of its type in existence, which is also the only dataset of citations annotated by authors and the only truly multidisciplinary dataset. Using this dataset, the shared task aims at classifying the citation context in research publications based on their influence and purpose. There will be two subtasks associated with this shared task. The subtask A is a multi-class classification problem, where citations are categorized into six different classes based on the purpose. The second subtask B is a binary classification task, based on the citation influence.