Transactions on Data Analysis in Social Science

Transactions on Data Analysis in Social Science

Assessment of Marital Satisfaction Using Support Vector Machine (SVM)

Document Type : Original Article

Authors
S. S. Mostafavi Alnouri 1
H. Houshmandan Behbahani 2
E. Divandari 3
1 Master’s Student in General Psychology, Islamic Azad University, Roudehen Branch, Tehran, Iran
2 Lecturer, Iranian Azin Steel Center, University of Applied Science and Technology, Tehran, Iran
3 Iranian Azin Steel Center, University of Applied Science and Technology, Tehran, Iran
10.47176/TDASS.2022.122
Abstract
The present study aimed to evaluate marital satisfaction using the Support Vector Machine (SVM) approach, a machine learning method known for its high classification accuracy. A cluster-randomized sample of 200 students from the Islamic Azad University, Science and Research Branch, Tehran, was selected to participate in the study. Marital satisfaction was assessed using the Enrich Marital Satisfaction Scale, a widely recognized instrument for evaluating relationship quality. Based on the results, participants reporting severe and low levels of satisfaction were classified into the “marital dissatisfaction” group, while those reporting moderate, high, and very high satisfaction were classified into the “marital satisfaction” group. Due to the relatively limited sample size, the SVM model was trained to perform binary classification and subsequently applied to predict outcomes for unobserved cases. Comparison of the model’s predictions with actual outcomes demonstrated a high level of accuracy, indicating the robustness and efficiency of the SVM approach in this context. The findings underscore the value of machine learning methods in psychological and social research, particularly in predicting complex constructs such as marital satisfaction. Furthermore, the application of SVM provides psychologists with a practical, cost-effective, and time-efficient tool for early identification of individuals at risk of marital dissatisfaction. This predictive capacity can contribute to the design of targeted counseling strategies, preventive measures, and evidence-based interventions that aim to strengthen family foundations and promote marital well-being.
Keywords
Marital Satisfaction
Support Vector Machine (SVM)
Enrich Questionnaire
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Transactions on Data Analysis in Social Science
Volume 4, Issue 3
Summer 2022
Pages 122-130

  • Receive Date 02 May 2022
  • Revise Date 14 July 2022
  • Accept Date 09 September 2022