Career guidance based on machine learning: social networks in professional identity construction

Earlier research has shown that personality traits can be predicted by mining social networks data. This paper describes the social constructivism grounds of machine learning methods in career guidance and broadens understanding role of social networks in psychological researches. The theoretical grounds are empirically confirmed by AUC-ROC measure calculation in career guidance modeling. Implications for career guidance practice will also be presented.