2020
COLING
COLING 2020
NLFIIT at SemEval-2020 Task 11: Neural Network Architectures for Detection of Propaganda Techniques in News Articles
Abstract
AbstractSince 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 competition: “Detection of Propaganda Techniques in News Articles”. We participated in both subtasks, propaganda span identification and propaganda technique classification. Our model utilizes recurrent Bi-LSTM layers with pre-trained word representations and also takes advantage of self-attention mechanism. Our model managed to achieve score 0.405 F1 for subtask 1 and 0.553 F1 for subtask 2 on test set resulting in 17th and 16th place in subtask 1 and subtask 2, respectively.
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Interdisciplinary Bridge
— Artificial Intelligence and Deep Learning and Machine Learning and Natural Language Processing
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Artificial Intelligence > Core AI > Memory
Machine Learning > Core Methods > Classification
Machine Learning > Optimization & Theory > Neural Network Optimization
Deep Learning > Architectures > Neural Networks
Deep Learning > Techniques > Pretraining
Natural Language Processing > Applications > Text Classification