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

Ipek Baris, Lukas Schmelzeisen, Steffen Staab


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.
Anthology ID:
S19-2193
Volume:
Proceedings of the 13th International Workshop on Semantic Evaluation
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota, USA
Venue:
*SEMEVAL
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1105–1109
URL:
https://www.aclweb.org/anthology/S19-2193
DOI:
10.18653/v1/S19-2193
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PDF:
https://www.aclweb.org/anthology/S19-2193.pdf