Determination of Women Voting Behavior: a Machine Learning Approach in the Turkish Political Arena

dc.contributor.author Caha, Havva
dc.contributor.author Bayyurt, Nizamettin
dc.date.accessioned 2021-09-10T11:58:22Z
dc.date.accessioned 2025-09-17T14:28:05Z
dc.date.available 2021-09-10T11:58:22Z
dc.date.available 2025-09-17T14:28:05Z
dc.date.issued 2020
dc.description Bayyurt, Nizamettin/0000-0001-6993-4715 en_US
dc.description.abstract Justice and Development Party (AKP) has been the ruling and biggest party in Turkey (AKP) since it has been established in 2002 and Republican People's Party (CHP) has been the main opposition party (CHP) since then. These two parties receive about 75% of all the votes. In Turkey half of the voters are females. In this study, the important attributes of women in party selection decisions are analyzed. To our knowledge, there is no such a study focusing on women's party preferences in Turkey. Additionally, this is one of the very few studies in Turkey concerning voters' party preferences. Therefore, this study aims to fill this gap in the literature. Center-periphery and social mobility theories are the two main theories explaining Turkish political life. The analyzed ideological, cultural, religious, social, economic and demographic characteristics of women supporters are selected according to these theories. Machine-learning techniques are employed as predictive tools. Results show that ideological attitudes like being leftist-rightist and religious values like headscarf, fasting in Ramadan, and praying are the most important effective attributes on party selection of women. However, socio-economic, cultural, educational and demographic atributes are not effective on party selection of women in Turkey. en_US
dc.identifier.doi 10.17583/rimcis.2020.5027
dc.identifier.issn 2014-3680
dc.identifier.scopus 2-s2.0-85097678394
dc.identifier.uri https://doi.org/10.17583/rimcis.2020.5027
dc.language.iso en en_US
dc.publisher Hipatia Press en_US
dc.relation.ispartof International and Multidisciplinary Journal of Social Sciences-Rimcis en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Women Voters en_US
dc.subject Machine Learning en_US
dc.subject AKP en_US
dc.subject CHP en_US
dc.subject Turkey en_US
dc.title Determination of Women Voting Behavior: a Machine Learning Approach in the Turkish Political Arena en_US
dc.title Determination of Women Voting Behavior: A Machine Learning Approach in the Turkish Political Arena
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Bayyurt, Nizamettin/0000-0001-6993-4715
gdc.author.wosid Bayyurt, Nizamettin/S-5583-2016
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.collaboration.industrial false
gdc.description.department Artuklu University en_US
gdc.description.departmenttemp [Caha, Havva] Mardin Artuklu Univ, Fac Econ & Adm & Sci, Mardin, Turkey; [Bayyurt, Nizamettin] Istanbul Tech Univ, Fac Management, Istanbul, Turkey en_US
gdc.description.endpage 288 en_US
gdc.description.issue 3 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q3
gdc.description.startpage 260 en_US
gdc.description.volume 9 en_US
gdc.description.woscitationindex Emerging Sources Citation Index
gdc.description.wosquality Q2
gdc.identifier.openalex W3084342406
gdc.identifier.wos WOS:000595527300003
gdc.index.type WoS en_US
gdc.index.type Scopus en_US
gdc.oaire.accesstype GOLD
gdc.oaire.diamondjournal false
gdc.oaire.impulse 0.0
gdc.oaire.influence 2.4895952E-9
gdc.oaire.isgreen true
gdc.oaire.keywords Women voters
gdc.oaire.keywords Turkey
gdc.oaire.keywords women voters, machine learning, AKP, CHP, Turkey
gdc.oaire.keywords CHP
gdc.oaire.keywords Social Sciences
gdc.oaire.keywords H
gdc.oaire.keywords machine learning
gdc.oaire.keywords AKP
gdc.oaire.popularity 1.3503004E-9
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 05 social sciences
gdc.oaire.sciencefields 0506 political science
gdc.openalex.collaboration National
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gdc.opencitations.count 0
gdc.plumx.mendeley 11
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relation.isOrgUnitOfPublication.latestForDiscovery 39ccb12e-5b2b-4b51-b989-14849cf90cae

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