@InProceedings{tan-card-smith:2017:Long,
  author    = {Tan, Chenhao  and  Card, Dallas  and  Smith, Noah A.},
  title     = {Friendships, Rivalries, and Trysts: Characterizing Relations between Ideas in Texts},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {773--783},
  abstract  = {Understanding how ideas relate to each other is a fundamental question in many
	domains, ranging from intellectual history to public communication. Because
	ideas are naturally embedded in texts, we propose the first framework to
	systematically characterize the relations between ideas based on their
	occurrence in a corpus of documents, independent of how these ideas are
	represented. Combining two statistics—cooccurrence within documents and
	prevalence correlation over time—our approach reveals a number of different
	ways in which ideas can cooperate and compete. For instance, two ideas can
	closely track each other’s prevalence over time, and yet rarely cooccur,
	almost like a “cold war” scenario. We observe that pairwise cooccurrence
	and prevalence correlation exhibit different distributions. We further
	demonstrate that our approach is able to uncover intriguing relations between
	ideas through in-depth case studies on news articles and research papers.},
  url       = {http://aclweb.org/anthology/P17-1072}
}