@inproceedings{wang-etal-2024-towards-quantifying,
title = "Towards quantifying politicization in foreign aid project reports",
author = "Wang, Sidi and
Eggers, Gustav and
de Roode Torres Georgiadis, Alexia and
{\DJ}o, Tuan Anh and
Gontard, L{\'e}a and
Carlitz, Ruth and
Bloem, Jelke",
editor = "Afli, Haithem and
Bouamor, Houda and
Casagran, Cristina Blasi and
Ghannay, Sahar",
booktitle = "Proceedings of the Second Workshop on Natural Language Processing for Political Sciences @ LREC-COLING 2024",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.politicalnlp-1.9",
pages = "85--90",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Towards quantifying politicization in foreign aid project reports
%A Wang, Sidi
%A Eggers, Gustav
%A de Roode Torres Georgiadis, Alexia
%A Đo, Tuan Anh
%A Gontard, Léa
%A Carlitz, Ruth
%A Bloem, Jelke
%Y Afli, Haithem
%Y Bouamor, Houda
%Y Casagran, Cristina Blasi
%Y Ghannay, Sahar
%S Proceedings of the Second Workshop on Natural Language Processing for Political Sciences @ LREC-COLING 2024
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F wang-etal-2024-towards-quantifying
%X 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.
%U https://aclanthology.org/2024.politicalnlp-1.9
%P 85-90
Markdown (Informal)
[Towards quantifying politicization in foreign aid project reports](https://aclanthology.org/2024.politicalnlp-1.9) (Wang et al., PoliticalNLP-WS 2024)
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.