What to Write? A topic recommender for journalists
Alessandro Cucchiarelli, Christian Morbidoni, Giovanni Stilo, Paola Velardi
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.- Anthology ID:
- W17-4204
- Volume:
- Proceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism
- Month:
- September
- Year:
- 2017
- Address:
- Copenhagen, Denmark
- Editors:
- Octavian Popescu, Carlo Strapparava
- Venue:
- WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 19–24
- Language:
- URL:
- https://aclanthology.org/W17-4204
- DOI:
- 10.18653/v1/W17-4204
- Cite (ACL):
- Alessandro Cucchiarelli, Christian Morbidoni, Giovanni Stilo, and Paola Velardi. 2017. What to Write? A topic recommender for journalists. In Proceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism, pages 19–24, Copenhagen, Denmark. Association for Computational Linguistics.
- Cite (Informal):
- What to Write? A topic recommender for journalists (Cucchiarelli et al., 2017)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/W17-4204.pdf