Know Who Your Friends Are: Understanding Social Connections from Unstructured Text
Léa Deleris, Francesca Bonin, Elizabeth Daly, Stéphane Deparis, Yufang Hou, Charles Jochim, Yassine Lassoued, Killian Levacher
Abstract
Having an understanding of interpersonal relationships is helpful in many contexts. Our system seeks to assist humans with that task, using textual information (e.g., case notes, speech transcripts, posts, books) as input. Specifically, our system first extracts qualitative and quantitative information elements (which we call signals) about interactions among persons, aggregates those to provide a condensed view of relationships and then enables users to explore all facets of the resulting social (multi-)graph through a visual interface.- Anthology ID:
- N18-5016
- 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:
- 76–80
- Language:
- URL:
- https://aclanthology.org/N18-5016
- DOI:
- 10.18653/v1/N18-5016
- Cite (ACL):
- Léa Deleris, Francesca Bonin, Elizabeth Daly, Stéphane Deparis, Yufang Hou, Charles Jochim, Yassine Lassoued, and Killian Levacher. 2018. Know Who Your Friends Are: Understanding Social Connections from Unstructured Text. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, pages 76–80, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- Know Who Your Friends Are: Understanding Social Connections from Unstructured Text (Deleris et al., NAACL 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/N18-5016.pdf