Keynote Abstract: Too soon? The limitations of AI for event data

Clionadh Raleigh


Abstract
Not all conflict datasets offer equal levels of coverage, depth, use-ability, and content. A review of the inclusion criteria, methodology, and sourcing of leading publicly available conflict datasets demonstrates that there are significant discrepancies in the output produced by ostensibly similar projects. This keynote will question the presumption of substantial overlap between datasets, and identify a number of important gaps left by deficiencies across core criteria for effective conflict data collection and analysis.
Anthology ID:
2020.aespen-1.2
Volume:
Proceedings of the Workshop on Automated Extraction of Socio-political Events from News 2020
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Ali Hürriyetoğlu, Erdem Yörük, Vanni Zavarella, Hristo Tanev
Venue:
AESPEN
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
7
Language:
English
URL:
https://aclanthology.org/2020.aespen-1.2
DOI:
Bibkey:
Cite (ACL):
Clionadh Raleigh. 2020. Keynote Abstract: Too soon? The limitations of AI for event data. In Proceedings of the Workshop on Automated Extraction of Socio-political Events from News 2020, page 7, Marseille, France. European Language Resources Association (ELRA).
Cite (Informal):
Keynote Abstract: Too soon? The limitations of AI for event data (Raleigh, AESPEN 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.aespen-1.2.pdf