CLEARumor at SemEval-2019 Task 7: ConvoLving ELMo Against Rumors

2019-04-05 · SEMEVAL 2019 6 · Ipek Baris, Lukas Schmelzeisen, Steffen Staab

This paper describes our submission to SemEval-2019 Task 7: RumourEval: Determining Rumor Veracity and Support for Rumors. We participated in both subtasks. The goal of subtask A is to classify the type of interaction between a rumorous social media post and a reply post as support, query, deny, or comment. The goal of subtask B is to predict the veracity of a given rumor. For subtask A, we implement a CNN-based neural architecture using ELMo embeddings of post text combined with auxiliary features and achieve a F1-score of 44.6%. For subtask B, we employ a MLP neural network leveraging our estimates for subtask A and achieve a F1-score of 30.1% (second place in the competition). We provide results and analysis of our system performance and present ablation experiments.

📄 PDF Abstract BibTeX arXiv:1904.03084

Code (1)

lschmelzeisen/clearumor 공식 구현 pytorch

Tasks

Rumour Detection

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