Digital Addiction Research Dataset

This dataset is created within the scope of Happy Project: A Socio-Technical Mining System That Measures Social Happiness", which is the Tübitak 1003 Priority Areas R&D project developed of 497 undergraduate students participating 304 female and 193 male. Dataset consisted of the result of the Oxford Happiness Questionnaire, Five Factor Personality Scale, Fear of Missing Out Scale, Smartphone Addiction Scale, and Social Media Addiction Scale.

The aim of research explore the effect of digital addiction on happiness using machine learning algorithm. For this reason, in the dataset the happiness attribute was truncated from the median value to two as happy and unhappy and represent it as target attribute. Random forests algorithm showed the best accuracy with 96% according to the results as a classification problems in this dataset.