Analyzing the Impact of the 2023 General Elections on Land Prices Using Machine Learning: a Case Study in Çanakkale, Turkey

dc.contributor.author Yalpır, Sükran
dc.contributor.author Genç, Levent Genc
dc.contributor.author Yucebas, Sait Can
dc.contributor.author Doğan, Simge
dc.date.accessioned 2025-05-11T18:40:09Z
dc.date.available 2025-05-11T18:40:09Z
dc.date.issued 2025
dc.description.abstract This study analyses the impact of the general elections to be held on 14 May 2023 on the real estate market in Turkey. The aim of the study is to develop a model to predict land unit prices (₺/m²) by analysing land prices, exchange rates and gold values observed before (February-March-April) and after (May-June-July) elections for Ayvacık, Bayramiç, Biga, Çan, Eceabat, Ezine, Gelibolu, Lapseki, Merkez and Yenice districts of Çanakkale province. Daily fluctuations in foreign exchange and gold values, which are the main economic parameters in the study, were recorded during the election period. The findings of this research, which predicts price movements in the property market using machine learning methods such as regression trees, reveal that unit prices of land generally tend to increase with increases in exchange rates, but in some districts where gold prices increase, the unit price shows a reverse trend. This is attributed to the fact that investors prefer gold as a safer asset in times of economic uncertainty. The results obtained can help investors and buyers to predict future trends in property prices, as well as contribute to the development of economic policies by experts to stabilise fluctuations in investment instruments. en_US
dc.identifier.doi 10.36306/konjes.1579931
dc.identifier.issn 2667-8055
dc.identifier.uri https://doi.org/10.36306/konjes.1579931
dc.identifier.uri https://search.trdizin.gov.tr/en/yayin/detay/1302724/analyzing-the-impact-of-the-2023-general-elections-on-land-prices-using-machine-learning-a-case-study-in-canakkale-turkey
dc.language.iso en en_US
dc.publisher Konya Teknik Univ en_US
dc.relation.ispartof Konya Mühendislik Bilimleri Dergisi (Online) en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Election en_US
dc.subject Sustainabilty Land Price en_US
dc.subject Economic Parameters en_US
dc.subject Regression Tree en_US
dc.subject Machine Learning en_US
dc.title Analyzing the Impact of the 2023 General Elections on Land Prices Using Machine Learning: a Case Study in Çanakkale, Turkey en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.wosid Yucebas, Sait/Jan-6981-2023
gdc.bip.impulseclass C5
gdc.bip.influenceclass C5
gdc.bip.popularityclass C5
gdc.coar.access open access
gdc.coar.type text::journal::journal article
gdc.description.department Konya Technical University en_US
gdc.description.departmenttemp Konya Teknik Üniversitesi,Çanakkale Onsekiz Mart Üniversitesi,Çanakkale Onsekiz Mart Üniversitesi,Çanakkale Onsekiz Mart Üniversitesi en_US
gdc.description.endpage 164 en_US
gdc.description.issue 1 en_US
gdc.description.publicationcategory Makale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality N/A
gdc.description.startpage 147 en_US
gdc.description.volume 13 en_US
gdc.description.woscitationindex Emerging Sources Citation Index
gdc.description.wosquality Q4
gdc.identifier.openalex W4408071135
gdc.identifier.trdizinid 1302724
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gdc.oaire.keywords Election;Sustainabilty Land Price;Economic Parameters;Regression Tree;Machine Learning
gdc.oaire.keywords Land Management
gdc.oaire.keywords Arazi Yönetimi
gdc.oaire.popularity 3.4988998E-9
gdc.oaire.publicfunded false
gdc.openalex.collaboration National
gdc.openalex.fwci 2.02156574
gdc.openalex.normalizedpercentile 0.76
gdc.openalex.toppercent TOP 10%
gdc.opencitations.count 0
gdc.plumx.mendeley 3
gdc.virtual.author Yalpır, Şükran
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