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
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
76–80
Language:
URL:
https://www.aclweb.org/anthology/N18-5016
DOI:
10.18653/v1/N18-5016
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/N18-5016.pdf