News Article Teaser Tweets and How to Generate Them
Computation and Language
2019-04-19 v2
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.(2017)'s seq2seq with pointer network.
Cite
@article{arxiv.1807.11535,
title = {News Article Teaser Tweets and How to Generate Them},
author = {Sanjeev Kumar Karn and Mark Buckley and Ulli Waltinger and Hinrich Schütze},
journal= {arXiv preprint arXiv:1807.11535},
year = {2019}
}