Determination of women’s voting behavior; A machine learning approach in the Turkish political arena

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 and half of the voters are females. 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. In this study, the important attributes of women in party selection decisions are analyzed. 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, socioeconomic, cultural, educational and demographic atributes are not effective on party selection of women in Turkey.