360° Stance Detection

Sebastian Ruder, John Glover, Afshin Mehrabani, Parsa Ghaffari


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° 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.
Anthology ID:
N18-5007
Volume:
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
31–35
Language:
URL:
https://aclanthology.org/N18-5007
DOI:
10.18653/v1/N18-5007
Bibkey:
Cite (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.
Cite (Informal):
360° Stance Detection (Ruder et al., NAACL 2018)
Copy Citation:
PDF:
https://aclanthology.org/N18-5007.pdf
Data
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