To the top

Page Manager: Webmaster
Last update: 9/11/2012 3:13 PM

Tell a friend about this page
Print version

Natural Language Processi… - University of Gothenburg, Sweden Till startsida
To content Read more about how we use cookies on

Natural Language Processing in Policy Evaluation: Extracting Policy Conditions from IMF Loan Agreements

Conference paper
Authors Joakim Åkerström
Adel Daoud
Richard Johansson
Published in Proceedings of the 22nd Nordic Conference on Computational Linguistics; September 30 – October 2; Turku, Finland
Publisher Linköping University Electronic Press
Publication year 2019
Published at Department of Computer Science and Engineering (GU)
Language en
Keywords natural language processing, text categorization, IMF, International Monetary Fund, methodology
Subject categories Computational linguistics, Other Social Sciences


Social science researchers often use text as the raw data in investigations: for instance, when investigating the effects of IMF policies on the development of countries under IMF programs, researchers typically encode structured descriptions of the programs using a time-consuming manual effort. Making this process automatic may open up new opportunities in scaling up such investigations. As a first step towards automatizing this coding process, we describe an experiment where we apply a sentence classifier that automatically detects mentions of policy conditions in IMF loan agreements and divides them into different types. The results show that the classifier is generally able to detect the policy conditions, although some types are hard to distinguish.

Page Manager: Webmaster|Last update: 9/11/2012

The University of Gothenburg uses cookies to provide you with the best possible user experience. By continuing on this website, you approve of our use of cookies.  What are cookies?