EACL 2021 WASSA 2021
11th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis
To be held in conjuntion with the EACL 2021  Conference

European Commission Joint Research Centre

University of Ghent


The CodaLab website on which the shared task will be run is now online: https://competitions.codalab.org/competitions/28713. All necessary information regarding the shared task can be found there.


Participants are given an extended release of the empathic reactions to news stories dataset which contains essays and Batson empathic concern and personal distress scores in reaction to news articles where there is harm to a person, group, or other (for more details see Buechel et al. 2018). The essays are between 300 and 800 characters in length. The extension of this dataset also includes person-level demographic information (age, gender, ethnicity, income, education level) as well as personality information. Additionally, we include emotion labels for the essays at both the document and sentence level, these emotion labels have been predicted automatically


The formulation of this task is to predict the Batson empathic concern ("feeling for someone"") and personal distress ("suffering with someone"") using the essay and any of the additional information, i.e. personality information, demographic information as well as the emotion labels.

The evaluation metric for this track is Pearson correlation with the gold ratings (overall, empathic concern, personal distress). Below is an example of essays and labels.

Track 1 examples
  • Development phase:
    • December 22: initial training data release
    • January 2021: launch codalab website
  • Test phase:
    • February 11 or 12: test data release
    • February 15: deadline submission final result
  • February 20: deadline system description paper (max. 4p)
  • March 1: notification of acceptance
  • March 7: Camera-ready papers due

You can download the development from this webpage. Please note that by downloading the data you agree to the following terms and conditions:

  • The organizers and their affiliated institutions makes no warranties regarding the datasets provided, including but not limited to being correct or complete. They cannot be held liable for providing access to the datasets or the usage of the datasets.
  • The datasets should only be used for scientific or research purposes. Any other use is explicitly prohibited.
  • The datasets must not be redistributed or shared in part or full with any third party. Redirect interested parties to this page.
  • f you use any of the datasets provided in the shared task, you agree to cite the associated papers. More information will be provided later.
abalahur.[at].gmail.com  |   Last updated: 10:00 14/01/2021
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