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CyberWallE at SemEval-2020 Task 11: An Analysis of Feature Engineering for Ensemble Models for Propaganda Detection

2020-08-22 15:51:16
Verena Blaschke, Maxim Korniyenko, Sam Tureski
arXiv_CL
             
Abstract

This paper describes our participation in the SemEval-2020 task Detection of Propaganda Techniques in News Articles. We participate in both subtasks: Span Identification (SI) and Technique Classification (TC). We use a bi-LSTM architecture in the SI subtask and train a complex ensemble model for the TC subtask. Our architectures are built using embeddings from BERT in combination with additional lexical features and extensive label post-processing. Our systems achieve a rank of 8 out of 35 teams in the SI subtask (F1-score: 43.86%) and 8 out of 31 teams in the TC subtask (F1-score: 57.37%).

Abstract (translated)

URL

https://arxiv.org/abs/2008.09859

PDF

https://arxiv.org/pdf/2008.09859.pdf

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