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
- 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
- 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)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/D19-1121.pdf