Scenario-based modeling of ontic personae for automatic personality perception

A model describing the wide variety of human behaviours called personality, is becoming increasingly popular among researchers due to the widespread availability of personal data generated from the use of prevalent digital devices, e.g., smartphones and wearables. Such an approach can be used to model an individual and even digitally clone a person, e.g., a Cyber-I (cyber individual), which can establish a unique and comprehensive description for an individual to mesh with various personalized services and applications. An extensive research literature on or related to personality computing exists, i.e., into automatic personality perception. However, the precision and integrity of current automatic personality perception is insufficient for the elaborate modeling in Cyber-I. Due to the heterogeneity of personal data, it is critical to classify the mass of personal data to valuable knowledge for sufficient personality perception. In addition, the precise calculation of personality based on such knowledge is also important. Therefore, this research is focused on designing scenario-based ontic personae as various individuals' facets in different situations for automatic personality perception. Using personal data, special scenarios, and based on specific ontic personae, our research is designed to ensure accurate modeling of ontic personae and personality perception.