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newsSweeper at SemEval-2020 Task 11: Context-Aware Rich Feature Representations For Propaganda Classification

21 Jul 2020SEMEVAL 2020arXiv:2007.10827archive 2025-07-28

Paramansh Singh, Siraj Sandhu, Subham Kumar, Ashutosh Modi

This paper describes our submissions to SemEval 2020 Task 11: Detection of Propaganda Techniques in News Articles for each of the two subtasks of Span Identification and Technique Classification. We make use of pre-trained BERT language model enhanced with tagging techniques developed for the task of Named Entity Recognition (NER), to develop a system for identifying propaganda spans in the text. For the second subtask, we incorporate contextual features in a pre-trained RoBERTa model for the classification of propaganda techniques. We were ranked 5th in the propaganda technique classification subtask.

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paramansh/propaganda_detection officialmentioned in papermentioned on GitHubpytorch report

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ArticlesClassificationGeneral ClassificationLanguage ModelingLanguage ModellingNERNamed Entity RecognitionNamed Entity Recognition (NER)named-entity-recognition

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AdamAttentionAttention DropoutBERTDense ConnectionsDropoutLayer NormalizationLinear LayerLinear Warmup With Linear DecayMulti-Head AttentionResidual ConnectionRoBERTaSoftmaxWeight DecayWordPiece

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