Personality Categorization of Big Five Personality Traits OCEAN Using K-Means Clustering

Our world has seen tremendous progress and change in the last couple of decades. The person’s personality observes the change during their lifetime. Acknowledging this helps us provide suitable recommendations to a person based on their personality for hobbies, education, work, etc. This work is the first step in this direction. The work uses the Big Five personality traits data comprised of 50 questions in 5 categories. The data is preprocessed for handling missing values and later normalized for adhering to the Gaussian distribution. The K-means clustering method is used for scientifically dividing data into meaningful clusters. The Elbow method is used to select the number of clusters. Obtained clusters confirm that K-means can separate the data into 5 clusters that represent five characteristics—openness, conscientiousness, extraversion, agreeableness, and neuroticism. Thus, a questionnaire of 50 questions can help us get insights about the responder for recommendations of various types.