@inproceedings{ruder-etal-2018-360deg,
title = "360{\textdegree} Stance Detection",
author = "Ruder, Sebastian and
Glover, John and
Mehrabani, Afshin and
Ghaffari, Parsa",
editor = "Liu, Yang and
Paek, Tim and
Patwardhan, Manasi",
booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Demonstrations",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://preview.aclanthology.org/fix-sig-urls/N18-5007/",
doi = "10.18653/v1/N18-5007",
pages = "31--35",
abstract = "The proliferation of fake news and filter bubbles makes it increasingly difficult to form an unbiased, balanced opinion towards a topic. To ameliorate this, we propose 360{\textdegree} Stance Detection, a tool that aggregates news with multiple perspectives on a topic. It presents them on a spectrum ranging from support to opposition, enabling the user to base their opinion on multiple pieces of diverse evidence."
}
Markdown (Informal)
[360° Stance Detection](https://preview.aclanthology.org/fix-sig-urls/N18-5007/) (Ruder et al., NAACL 2018)
ACL
- Sebastian Ruder, John Glover, Afshin Mehrabani, and Parsa Ghaffari. 2018. 360° Stance Detection. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, pages 31–35, New Orleans, Louisiana. Association for Computational Linguistics.