SemEval-2020 Task 11

Detection of Propaganda Techniques in News Articles

authored by

Giovanni da San Martino, Alberto Barrón-Cedeño, Henning Wachsmuth, Rostislav Petrov, Preslav Nakov

Abstract

We present the results and the main findings of SemEval-2020 Task 11 on Detection of Propaganda Techniques in News Articles. The task featured two subtasks. Subtask SI is about Span Identification: given a plain-text document, spot the specific text fragments containing propaganda. Subtask TC is about Technique Classification: given a specific text fragment, in the context of a full document, determine the propaganda technique it uses, choosing from an inventory of 14 possible propaganda techniques. The task attracted a large number of participants: 250 teams signed up to participate and 44 made a submission on the test set. In this paper, we present the task, analyze the results, and discuss the system submissions and the methods they used. For both subtasks, the best systems used pre-trained Transformers and ensembles.

External Organisation(s)

Qatar Computing Research institute
University of Bologna
Paderborn University
A Data Pro

Type

Conference contribution

Pages

1377-1414

No. of pages

38

Publication date

12.2020

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Theoretical Computer Science, Computational Theory and Mathematics, Computer Science Applications

Electronic version(s)

https://doi.org/10.48550/arXiv.2009.02696 (Access: Open)
https://doi.org/10.18653/v1/2020.semeval-1.186 (Access: Open)