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Determination of Voting Tendencies in Turkey through Data Mining Algorithms

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  • Ali Bayır

    (Informatics Department, Istanbul University, Istanbul, Turkey)

  • Sebnem Ozdemir

    (Informatics Department, Istanbul University, Istanbul, Turkey)

  • Sevinç Gülseçen

    (Informatics Department, Istanbul University, Istanbul, Turkey)

Abstract

Political elections can be defined as systems that contain political tendencies and voters' perceptions and preferences. The outputs of those systems are formed by specific attributes of individuals such as age, gender, occupancy, educational status, socio-economic status, religious belief, etc. Those attributes can create a data set, which contains hidden information and undiscovered patterns that can be revealed by using data mining methods and techniques. The main purpose of this study is to define voting tendencies in politics by using some of data mining methods. According to that purpose, the survey results, which were prepared and applied before 2011 elections of Turkey by KONDA Research and Consultancy Company, were used as raw data set. After Preprocessing of data, models were generated via data mining algorithms, such as Gini, C4.5 Decision Tree, Naive Bayes and Random Forest. Because of increasing popularity and flexibility in analyzing process, R language and Rstudio environment were used.

Suggested Citation

  • Ali Bayır & Sebnem Ozdemir & Sevinç Gülseçen, 2017. "Determination of Voting Tendencies in Turkey through Data Mining Algorithms," International Journal of E-Adoption (IJEA), IGI Global, vol. 9(1), pages 50-58, January.
    • Handle: RePEc:igg:jea000:v:9:y:2017:i:1:p:50-58
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