NSIT@NLP4IF-2019: Propaganda Detection from News Articles using Transfer Learning
In this paper, we describe our approach and system description for NLP4IF 2019 Workshop: Shared Task on Fine-Grained Propaganda Detection. Given a sentence from a news article, the task is to detect whether the sentence contains a propagandistic agenda or not. The main contribution of our work is to evaluate the effectiveness of various transfer learning approaches like ELMo, BERT, and RoBERTa for propaganda detection. We show the use of Document Embeddings on the top of Stacked Embeddings combined with LSTM for identification of propagandistic context in the sentence. We further provide analysis of these models to show the effect of oversampling on the provided dataset. In the final test-set evaluation, our system ranked 21st with F1-score of 0.43 in the SLC Task.
Code (0)
등록된 구현이 없습니다.
Tasks
ArticlesPropaganda detectionSentenceTransfer LearningMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
UAIC1860 at SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles
The {``}Detection of Propaganda Techniques in News Articles{''} task at the SemEval 2020 competition focuses on detecting and classifying propaganda, pervasive in news article. In this paper, we present a system able to …
ArticlesSentenceNLFIIT at SemEval-2020 Task 11: Neural Network Architectures for Detection of Propaganda Techniques in News Articles
Since propaganda became more common technique in news, it is very important to look for possibilities of its automatic detection. In this paper, we present neural model architecture submitted to the SemEval-2020 Task 11 …
ArticlesPropaganda span identificationSentence-Level Propaganda Detection in News Articles with Transfer Learning and BERT-BiLSTM-Capsule Model
In recent years, the need for communication increased in online social media. Propaganda is a mechanism which was used throughout history to influence public opinion and it is gaining a new dimension with the rising inte…
ArticlesEmotion ClassificationGeneral ClassificationPropaganda detection+2UPB at SemEval-2020 Task 11: Propaganda Detection with Domain-Specific Trained BERT
Manipulative and misleading news have become a commodity for some online news outlets and these news have gained a significant impact on the global mindset of people. Propaganda is a frequently employed manipulation meth…
ArticlesPropaganda detectionPropaganda span identificationInno at SemEval-2020 Task 11: Leveraging Pure Transformer for Multi-Class Propaganda Detection
The paper presents the solution of team "Inno" to a SEMEVAL 2020 task 11 "Detection of propaganda techniques in news articles". The goal of the second subtask is to classify textual segments that correspond to one of the…
ArticlesPropaganda detection