@InProceedings{jaech-hathi-ostendorf:2018:N18-2,
  author    = {Jaech, Aaron  and  Hathi, Shobhit  and  Ostendorf, Mari},
  title     = {Community Member Retrieval on Social Media Using Textual Information},
  booktitle = {Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {595--601},
  abstract  = {This paper addresses the problem of community membership detection using only text features in a scenario where a small number of positive labeled examples defines the community. The solution introduces an unsupervised proxy task for learning user embeddings: user re-identification. Experiments with 16 different communities show that the resulting embeddings are more effective for community membership identification than common unsupervised representations.},
  url       = {http://www.aclweb.org/anthology/N18-2094}
}