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

arXiv: https://arxiv.org/abs/2007.10827 · HTML: https://mlsanity.com/paper/2007.10827/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jul 2020.

## Built on by (most cited first, 2 of 2)

- [Hierarchical Multi-Instance Multi-Label Learning for Detecting Propaganda Techniques](https://mlsanity.com/paper/2305.19419/) (2023)
- [IITK at SemEval-2024 Task 4: Hierarchical Embeddings for Detection of Persuasion Techniques in Memes](https://mlsanity.com/paper/2404.04520/) (2024)

## Abstract (arXiv)

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.