@InProceedings{cheng-fang-ostendorf:2017:EMNLP2017,
  author    = {Cheng, Hao  and  Fang, Hao  and  Ostendorf, Mari},
  title     = {A Factored Neural Network Model for Characterizing Online Discussions in Vector Space},
  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     = {2296--2306},
  abstract  = {We develop a novel factored neural model that learns comment embeddings in an
	unsupervised way leveraging the structure of distributional context in online
	discussion forums. The model links different context with related language
	factors in the embedding space, providing a way to interpret the factored
	embeddings. Evaluated on a community endorsement prediction task using a large
	collection of topic-varying Reddit discussions, the factored embeddings
	consistently achieve improvement over other text representations. Qualitative
	analysis shows that the model captures community style and topic, as well as
	response trigger patterns.},
  url       = {https://www.aclweb.org/anthology/D17-1243}
}