Natural Language Processing for Achieving Sustainable Development: the Case of Neural Labelling to Enhance Community Profiling
Costanza Conforti, Stephanie Hirmer, Dai Morgan, Marco Basaldella, Yau Ben Or
Abstract
In recent years, there has been an increasing interest in the application of Artificial Intelligence – and especially Machine Learning – to the field of Sustainable Development (SD). However, until now, NLP has not been systematically applied in this context. In this paper, we show the high potential of NLP to enhance project sustainability. In particular, we focus on the case of community profiling in developing countries, where, in contrast to the developed world, a notable data gap exists. Here, NLP could help to address the cost and time barrier of structuring qualitative data that prohibits its widespread use and associated benefits. We propose the new extreme multi-class multi-label Automatic UserPerceived Value classification task. We release Stories2Insights, an expert-annotated dataset of interviews carried out in Uganda, we provide a detailed corpus analysis, and we implement a number of strong neural baselines to address the task. Experimental results show that the problem is challenging, and leaves considerable room for future research at the intersection of NLP and SD.- Anthology ID:
- 2020.emnlp-main.677
- Volume:
- Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Bonnie Webber, Trevor Cohn, Yulan He, Yang Liu
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 8427–8444
- Language:
- URL:
- https://aclanthology.org/2020.emnlp-main.677
- DOI:
- 10.18653/v1/2020.emnlp-main.677
- Cite (ACL):
- Costanza Conforti, Stephanie Hirmer, Dai Morgan, Marco Basaldella, and Yau Ben Or. 2020. Natural Language Processing for Achieving Sustainable Development: the Case of Neural Labelling to Enhance Community Profiling. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 8427–8444, Online. Association for Computational Linguistics.
- Cite (Informal):
- Natural Language Processing for Achieving Sustainable Development: the Case of Neural Labelling to Enhance Community Profiling (Conforti et al., EMNLP 2020)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2020.emnlp-main.677.pdf