Sustainable Economic Development Through Crisis Detection Using AI Techniques

Kurban Kotan and Serdar Kırışoğlu ()
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Kurban Kotan: Department of Electrical-Electronics and Computer Engineering, Düzce University, 81620 Düzce, Türkiye
Serdar Kırışoğlu: Department of Computer Engineering, Düzce University, 81620 Düzce, Türkiye

Sustainability, 2025, vol. 17, issue 4, 1-23

Abstract: Economics is based on data and indicators. Although their interpretation can be complicated, their effects can be calculated in advance. In other words, economic crises are not as complicated and unpredictable as natural disasters. If economic news, news that reflects the thoughts of society, and especially the experiences and predictions of economic experts, is semantically processed from the news texts written by economic experts, economic crises can be predicted long in advance. In addition, the frequency of news about crises in society is also effective. Events that affect society are often mentioned. This can be an indication of some economic crises. In this research, we attempted to detect the economic crises and inflation increases in Turkey in December 2021 and in Germany in September 2022 several months in advance with natural language processing (NLP) models. In the study, the daily news retrieved via RSS from the leading news channels and newspapers was first preprocessed and then the similarities were checked with NLP models. Finally, similarities and changes were analyzed in comparison with inflation data. It was found that similar changes a few months ago had a high correlation with inflation data.

Keywords: natural language processing; sentence embedding; language representation models; economic crisis; news data (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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