Developing Personality Traits through Social Media Analysis

Abstract

The rise of social media platforms such as Facebook has enabled the prediction of personality traits through digital footprints. Traditional personality assessments used questionnaires, but recent advances in machine learning allow for more precise predictions by analyzing text data. This study uses Facebook status updates to predict the big five personality traits: openness, conscientiousness, extraversion, agreeableness, and neuroticism through logistic regression models. The dataset consists of 9,917 status posts from 250 individuals. We use feature extraction methods like TF-IDF and word embeddings for text representation. Model performance is evaluated with accuracy, precision, recall, and F1-score metrics. This research highlights practical applications in personalized marketing, mental health support, and user engagement while addressing ethical concerns related to data privacy and responsible use.