News Article Teaser Tweets and How to Generate Them
Sanjeev Kumar Karn, Mark Buckley, Ulli Waltinger, Hinrich Schütze
Abstract
In this work, we define the task of teaser generation and provide an evaluation benchmark and baseline systems for the process of generating teasers. A teaser is a short reading suggestion for an article that is illustrative and includes curiosity-arousing elements to entice potential readers to read particular news items. Teasers are one of the main vehicles for transmitting news to social media users. We compile a novel dataset of teasers by systematically accumulating tweets and selecting those that conform to the teaser definition. We have compared a number of neural abstractive architectures on the task of teaser generation and the overall best performing system is See et al. seq2seq with pointer network.- Anthology ID:
- N19-1398
- Volume:
- Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
- Month:
- June
- Year:
- 2019
- Address:
- Minneapolis, Minnesota
- Editors:
- Jill Burstein, Christy Doran, Thamar Solorio
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 3967–3977
- Language:
- URL:
- https://aclanthology.org/N19-1398
- DOI:
- 10.18653/v1/N19-1398
- Cite (ACL):
- Sanjeev Kumar Karn, Mark Buckley, Ulli Waltinger, and Hinrich Schütze. 2019. News Article Teaser Tweets and How to Generate Them. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 3967–3977, Minneapolis, Minnesota. Association for Computational Linguistics.
- Cite (Informal):
- News Article Teaser Tweets and How to Generate Them (Karn et al., NAACL 2019)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/N19-1398.pdf
- Code
- sanjeevkrn/teaser_collect + additional community code