@InProceedings{goyal-EtAl:2017:EMNLP2017,
  author    = {Goyal, Tanya  and  Kelkar, Sachin  and  Agarwal, Manas  and  Grover, Jeenu},
  title     = {An Empirical Analysis of Edit Importance between Document Versions},
  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     = {2780--2784},
  abstract  = {In this paper, we present a novel approach to infer significance of various
	textual  edits to documents. An author may make several edits to a document;
	each edit varies in its impact to the content of the document. While some edits
	are surface changes and introduce negligible change, other edits may change the
	content/tone of the document significantly. In this paper, we perform an
	analysis on the human perceptions of edit importance while reviewing documents
	from one version to the next. We identify linguistic features that influence
	edit importance and model it in a regression based setting. We show that the
	predicted importance by our approach is highly correlated with the human
	perceived importance, established by a Mechanical Turk study.},
  url       = {https://www.aclweb.org/anthology/D17-1295}
}