@InProceedings{srivastava-rehm-morenoschneider:2017:SemEval,
  author    = {Srivastava, Ankit  and  Rehm, Georg  and  Moreno Schneider, Julian},
  title     = {DFKI-DKT at SemEval-2017 Task 8: Rumour Detection and Classification using Cascading Heuristics},
  booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {486--490},
  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.},
  url       = {http://www.aclweb.org/anthology/S17-2085}
}