3218IR at SemEval-2020 Task 11: Conv1D and Word Embedding in Propaganda Span Identification at News Articles
Dimas Sony Dewantara, Indra Darmawan Budi, Muhammad Okky Ibrohim · 2020
In this paper, we present the result of our experiment with a variant of 1 Dimensional Convolutional Neural Network (Conv1D) hyper-parameters value.We describe the system entered by the team of Information Retrieval Lab.Universitas Indonesia (3218IR) in the SemEval 2020 Task 11 Sub Task 1 about propaganda span identification in news articles.The best model obtained an F1 score of 0.24 in the development set and 0.23 in the test set.We show that there is a potential for performance improvement through the use of models with appropriate hyper-parameters.Our system uses a combination of Conv1D and GloVe as Word Embedding to detect propaganda in the fragment text level.