@InProceedings{menini-EtAl:2017:EMNLP2017,
  author    = {Menini, Stefano  and  Nanni, Federico  and  Ponzetto, Simone Paolo  and  Tonelli, Sara},
  title     = {Topic-Based Agreement and Disagreement in US Electoral Manifestos},
  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     = {2938--2944},
  abstract  = {We present a topic-based analysis of agreement and disagreement in political
	manifestos, which relies on a new method for topic detection based on key
	concept  clustering. Our approach outperforms both standard techniques like LDA
	and a state-of-the-art graph-based method, and provides promising initial
	results for this new task in computational social science.},
  url       = {https://www.aclweb.org/anthology/D17-1318}
}