Towards quantifying politicization in foreign aid project reports

Sidi Wang, Gustav Eggers, Alexia de Roode Torres Georgiadis, Tuan Anh Đo, Léa Gontard, Ruth Carlitz, Jelke Bloem


Abstract
We aim to develop a metric of politicization by investigating whether this concept can be operationalized computationally using document embeddings. We are interested in measuring the extent to which foreign aid is politicized. Textual reports of foreign aid projects are often made available by donor governments, but these are large and unstructured. By embedding them in vector space, we can compute similarities between sets of known politicized keywords and the foreign aid reports. We present a pilot study where we apply this metric to USAID reports.
Anthology ID:
2024.politicalnlp-1.9
Volume:
Proceedings of the Second Workshop on Natural Language Processing for Political Sciences @ LREC-COLING 2024
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Haithem Afli, Houda Bouamor, Cristina Blasi Casagran, Sahar Ghannay
Venues:
PoliticalNLP | WS
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
85–90
Language:
URL:
https://aclanthology.org/2024.politicalnlp-1.9
DOI:
Bibkey:
Cite (ACL):
Sidi Wang, Gustav Eggers, Alexia de Roode Torres Georgiadis, Tuan Anh Đo, Léa Gontard, Ruth Carlitz, and Jelke Bloem. 2024. Towards quantifying politicization in foreign aid project reports. In Proceedings of the Second Workshop on Natural Language Processing for Political Sciences @ LREC-COLING 2024, pages 85–90, Torino, Italia. ELRA and ICCL.
Cite (Informal):
Towards quantifying politicization in foreign aid project reports (Wang et al., PoliticalNLP-WS 2024)
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PDF:
https://aclanthology.org/2024.politicalnlp-1.9.pdf