@InProceedings{vilares-he:2017:EMNLP2017,
  author    = {Vilares, David  and  He, Yulan},
  title     = {Detecting Perspectives in Political Debates},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {1573--1582},
  abstract  = {We explore how to detect people's perspectives that occupy a certain
	proposition. We propose a Bayesian modelling approach where topics (or
	propositions) and their associated perspectives (or viewpoints) are modeled as
	latent variables. Words associated with topics or perspectives follow different
	generative routes. Based on the extracted perspectives, we can extract the top
	associated sentences from text to generate a succinct summary which allows a
	quick glimpse of the main viewpoints in a document. The model is evaluated on
	debates from the House of Commons of the UK Parliament, revealing perspectives
	from the debates without the use of labelled data and obtaining better results
	than previous related solutions under a variety of evaluations.},
  url       = {https://www.aclweb.org/anthology/D17-1165}
}