Measure Country-Level Socio-Economic Indicators with Streaming News: An Empirical Study

Bonan Min, Xiaoxi Zhao


Abstract
Socio-economic conditions are difficult to measure. For example, the U.S. Bureau of Labor Statistics needs to conduct large-scale household surveys regularly to track the unemployment rate, an indicator widely used by economists and policymakers. We argue that events reported in streaming news can be used as “micro-sensors” for measuring socio-economic conditions. Similar to collecting surveys and then counting answers, it is possible to measure a socio-economic indicator by counting related events. In this paper, we propose Event-Centric Indicator Measure (ECIM), a novel approach to measure socio-economic indicators with events. We empirically demonstrate strong correlation between ECIM values to several representative indicators in socio-economic research.
Anthology ID:
D19-1121
Volume:
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Month:
November
Year:
2019
Address:
Hong Kong, China
Editors:
Kentaro Inui, Jing Jiang, Vincent Ng, Xiaojun Wan
Venues:
EMNLP | IJCNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
1249–1254
Language:
URL:
https://aclanthology.org/D19-1121
DOI:
10.18653/v1/D19-1121
Bibkey:
Cite (ACL):
Bonan Min and Xiaoxi Zhao. 2019. Measure Country-Level Socio-Economic Indicators with Streaming News: An Empirical Study. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 1249–1254, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Measure Country-Level Socio-Economic Indicators with Streaming News: An Empirical Study (Min & Zhao, EMNLP-IJCNLP 2019)
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PDF:
https://aclanthology.org/D19-1121.pdf