@InProceedings{cucchiarelli-EtAl:2017:NLPmJ,
  author    = {Cucchiarelli, Alessandro  and  Morbidoni, Christian  and  Stilo, Giovanni  and  Velardi, Paola},
  title     = {What to Write? A topic recommender for journalists},
  booktitle = {Proceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {19--24},
  abstract  = {In this paper we present a recommender
	system, What To Write and Why, capable
	of suggesting to a journalist, for a given
	event, the aspects still uncovered in news
	articles on which the readers focus their interest.
	The basic idea is to characterize an
	event according to the echo it receives in
	online news sources and associate it with
	the corresponding readers’ communicative
	and informative patterns, detected through
	the analysis of Twitter and Wikipedia, respectively.
	Our methodology temporally
	aligns the results of this analysis and recommends
	the concepts that emerge as topics
	of interest from Twitter andWikipedia,
	either not covered or poorly covered in the
	published news articles.},
  url       = {http://www.aclweb.org/anthology/W17-4204}
}