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

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

5 Apr 2019SEMEVAL 2019 6arXiv:1904.03084archive 2025-07-28

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.

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Rumour Detection

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Methods

BiLSTMELMoLSTMSigmoid ActivationSoftmaxTanh Activation

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