paper-with-me

Papers

BPGC at SemEval-2020 Task 11: Propaganda Detection in News Articles with Multi-Granularity Knowledge Sharing and Linguistic Features based Ensemble Learning

2020-05-31 · SEMEVAL 2020 · Rajaswa Patil, Somesh Singh, Swati Agarwal

Propaganda spreads the ideology and beliefs of like-minded people, brainwashing their audiences, and sometimes leading to violence. SemEval 2020 Task-11 aims to design automated systems for news propaganda detection. Task-11 consists of two sub-tasks, namely, Span Identification - given any news article, the system tags those specific fragments which contain at least one propaganda technique; and Technique Classification - correctly classify a given propagandist statement amongst 14 propaganda techniques. For sub-task 1, we use contextual embeddings extracted from pre-trained transformer models to represent the text data at various granularities and propose a multi-granularity knowledge sharing approach. For sub-task 2, we use an ensemble of BERT and logistic regression classifiers with linguistic features. Our results reveal that the linguistic features are the strong indicators for covering minority classes in a highly imbalanced dataset.

📄 PDF Abstract BibTeX arXiv:2006.00593

Code (0)

등록된 구현이 없습니다.

Tasks

ArticlesEnsemble LearningPropaganda detectionTask 2

Methods 이 논문이 사용한 방법론

Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.
Absolute Position Encodings Absolute Position Encodings are a type of position embeddings for [Transformer-based models] where positional encodings are…
Position-Wise Feed-Forward Layer 설명 없음
Weight Decay 설명 없음
Refunds@Expedia|||How do I get a full refund from Expedia? “How do I get a full refund from Expedia? How do I get a full refund from Expedia? – Call ☎️ +1-(888) 829 (0881) or +1-805-330-4056 or +1-805-330-4056 for Quick Help &…
Attention Dropout Attention Dropout is a type of dropout used in attention-based architectures, where elements are randomly dropped out of the…
Linear Warmup With Linear Decay Linear Warmup With Linear Decay is a learning rate schedule in which we increase the learning rate linearly for $n$ updates and then linearly decay afterwards.
WordPiece 설명 없음

Similar Papers 제목 키워드 기반

UAIC1860 at SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles

2020-12-01 · SEMEVAL 2020 · Vlad Ermurachi, Daniela Gifu

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 …

ArticlesSentence

NLFIIT at SemEval-2020 Task 11: Neural Network Architectures for Detection of Propaganda Techniques in News Articles

2020-12-01 · SEMEVAL 2020 · Matej Martinkovic, Samuel Pecar, Marian Simko

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 identification

Inno at SemEval-2020 Task 11: Leveraging Pure Transformer for Multi-Class Propaganda Detection

2020-08-26 · Dmitry Grigorev, Vladimir Ivanov

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

UPB at SemEval-2020 Task 11: Propaganda Detection with Domain-Specific Trained BERT

2020-09-11 · SEMEVAL 2020 · Andrei Paraschiv, Dumitru-Clementin Cercel, Mihai Dascalu

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 identification

Inno at SemEval-2020 Task 11: Leveraging Pure Transfomer for Multi-Class Propaganda Detection

2020-12-01 · SEMEVAL 2020 · Dmitry Grigorev, Vladimir Ivanov

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 t…

ArticlesPropaganda detection