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    <abstract>This paper presents our systems for SemEval 2020 Shared Task 11: Detection of Propaganda Techniques in News Articles. We participate in both the span identification and technique classification subtasks and report on experiments using different BERT-based models along with handcrafted features. Our models perform well above the baselines for both tasks, and we contribute ablation studies and discussion of our results to dissect the effectiveness of different features and techniques with the goal of aiding future studies in propaganda detection.</abstract>
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%0 Conference Proceedings
%T Team DoNotDistribute at SemEval-2020 Task 11: Features, Finetuning, and Data Augmentation in Neural Models for Propaganda Detection in News Articles
%A Kranzlein, Michael
%A Behzad, Shabnam
%A Goharian, Nazli
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 dec
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F kranzlein-etal-2020-team
%X This paper presents our systems for SemEval 2020 Shared Task 11: Detection of Propaganda Techniques in News Articles. We participate in both the span identification and technique classification subtasks and report on experiments using different BERT-based models along with handcrafted features. Our models perform well above the baselines for both tasks, and we contribute ablation studies and discussion of our results to dissect the effectiveness of different features and techniques with the goal of aiding future studies in propaganda detection.
%R 10.18653/v1/2020.semeval-1.196
%U https://aclanthology.org/2020.semeval-1.196
%U https://doi.org/10.18653/v1/2020.semeval-1.196
%P 1502-1508

Markdown (Informal)

[Team DoNotDistribute at SemEval-2020 Task 11: Features, Finetuning, and Data Augmentation in Neural Models for Propaganda Detection in News Articles](https://aclanthology.org/2020.semeval-1.196) (Kranzlein et al., SemEval 2020)

• Team DoNotDistribute at SemEval-2020 Task 11: Features, Finetuning, and Data Augmentation in Neural Models for Propaganda Detection in News Articles (Kranzlein et al., SemEval 2020)

ACL

• Michael Kranzlein, Shabnam Behzad, and Nazli Goharian. 2020. Team DoNotDistribute at SemEval-2020 Task 11: Features, Finetuning, and Data Augmentation in Neural Models for Propaganda Detection in News Articles. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1502–1508, Barcelona (online). International Committee for Computational Linguistics.