Abstract
We describe our submissions for SemEval-2017 Task 8, Determining Rumour Veracity and Support for Rumours. The Digital Curation Technologies (DKT) team at the German Research Center for Artificial Intelligence (DFKI) participated in two subtasks: Subtask A (determining the stance of a message) and Subtask B (determining veracity of a message, closed variant). In both cases, our implementation consisted of a Multivariate Logistic Regression (Maximum Entropy) classifier coupled with hand-written patterns and rules (heuristics) applied in a post-process cascading fashion. We provide a detailed analysis of the system performance and report on variants of our systems that were not part of the official submission.- Anthology ID:
- S17-2085
- Volume:
- Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
- Month:
- August
- Year:
- 2017
- Address:
- Vancouver, Canada
- Editors:
- Steven Bethard, Marine Carpuat, Marianna Apidianaki, Saif M. Mohammad, Daniel Cer, David Jurgens
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 486–490
- Language:
- URL:
- https://aclanthology.org/S17-2085
- DOI:
- 10.18653/v1/S17-2085
- Cite (ACL):
- Ankit Srivastava, Georg Rehm, and Julian Moreno Schneider. 2017. DFKI-DKT at SemEval-2017 Task 8: Rumour Detection and Classification using Cascading Heuristics. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 486–490, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- DFKI-DKT at SemEval-2017 Task 8: Rumour Detection and Classification using Cascading Heuristics (Srivastava et al., SemEval 2017)
- PDF:
- https://preview.aclanthology.org/naacl24-info/S17-2085.pdf