Automatic personality prediction: an enhanced method using ensemble modeling

Human personality is significantly represented by those words which he/she uses in his/her speech or writing. As a consequence of spreading the information infrastructures (specifically Internet and social media), human communications have reformed notably from face to communication. Generally, Automatic Personality Prediction (or Perception) (APP) automated forecasting on different types generated/exchanged contents (like text, speech, image, video, etc.). The major objective this study enhance accuracy APP text. To end, we suggest five new methods including term frequency vector-based, ontology-based, enriched latent semantic analysis (LSA)-based, deep learning-based (BiLSTM) methods. These as base ones, contribute each other through ensemble modeling (stacking) based hierarchical attention network (HAN) meta-model. results show that enhances APP.