Analysis of Turkey's Demographic and Social Structure Using PCA And K-Means Clustering

This study aims to investigate the demographic and socioeconomic inequalities in the provinces by taking advantage of Turkey's unique location and complex society and comprehensively analyzing the demographic and socioeconomic structure of the provinces in Turkey. A multidimensional data set containing the data of 81 provinces between 2010 and 2022, provided as open data by TUIK (Turkish Statistical Institute) for the purpose, uses advanced data such as Exploratory Data Analysis (EDA), Principal Component Analysis (PCA) and K-Means clustering. Were examined using data analysis techniques. The study discussed fundamental socioeconomic indicators such as internal migration, population growth, foreign population density, and divorce rates. The analysis results reveal significant differences between cities regarding migration patterns, population growth rate, and socioeconomic characteristics. PCA and cluster analysis provided a more detailed understanding of these differences by grouping towns according to their demographic and socioeconomic profiles. The study provides essential information regarding Turkey's population dynamics and social fabric, developing effective local and national policies and strengthening social cohesion. Looking at the results, it was revealed that some precautions should be taken. Particular attention should be given to urban planning, education, health, and social services, considering the multidimensional structure of demographic and socioeconomic profiles. In regions with intense migration flows, priority should be given to strengthening social services, increasing economic opportunities, and developing integration policies. The population growth rate is low or negative. Measures to encourage population growth and strategies to support economic development should be implemented in the regions where it is located.