CLEARumor at SemEval-2019 Task 7: ConvoLving ELMo Against Rumors
TL
TL;DR
This paper describes the submission to SemEval-2019 Task 7: RumourEval: Determining Rumor Veracity and Support for Rumors, and provides results and analysis of the system performance and present ablation experiments.
Abstract
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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SemEval-2019 Task 7: RumourEval, Determining Rumour Veracity and Support for Rumours
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