International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 174 - Number 10 |
Year of Publication: 2021 |
Authors: Jayshri Patil, Jikitsha Sheth |
10.5120/ijca2021920968 |
Jayshri Patil, Jikitsha Sheth . Comparative Study of Data Sources, Features, and Approaches for Automatic Personality Classification from Text. International Journal of Computer Applications. 174, 10 ( Jan 2021), 17-23. DOI=10.5120/ijca2021920968
Personality is a concern with individual differences in characteristic patterns of thinking, feeling, and behavior. Computational recognition of user personality is likely to be useful in many computational applications and technologies such as career counseling, relationship, and health counseling, human resource management, forensics, and mental health diagnosis. It involves understanding, prediction, and analysis of human behavior. The different methods have been proposed to automatically infer the user's personality from their user generated content. The paper discusses state-of-the-art personality recognition on various data sources, features, and their impact on different application areas.