@InProceedings{bahuleyan-vechtomova:2017:SemEval,
  author    = {Bahuleyan, Hareesh  and  Vechtomova, Olga},
  title     = {UWaterloo at SemEval-2017 Task 8: Detecting Stance towards Rumours with Topic Independent Features},
  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     = {461--464},
  abstract  = {This paper describes our system for subtask-A: SDQC for RumourEval, task-8 of
	SemEval 2017. Identifying rumours, especially for breaking news events as they
	unfold, is a challenging task due to the absence of sufficient information
	about the exact rumour stories circulating on social media. Determining the
	stance of Twitter users towards rumourous messages could provide an indirect
	way of identifying potential rumours. The proposed approach makes use of topic
	independent features from two categories, namely cue features and message
	specific features to fit a gradient boosting classifier. With an accuracy of
	0.78, our system achieved the second best performance on subtask-A of
	RumourEval.},
  url       = {http://www.aclweb.org/anthology/S17-2080}
}