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
- Editors:
- Yang Liu, Tim Paek, Manasi Patwardhan
- 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
- 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)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/N18-5007.pdf
- Data
- DBpedia