DescriptionAutomatic personality prediction is getting more popular because it is convenient and reliable. Lexicon-based analysis has been successful in the fields of sentiment analysis and emotion. Many studies have used linear models for personality prediction, which suggests that we can also use lexical-based analysis for personality prediction. In the current study, we developed weighted word lexicons (words and scores) on each dimension of MBTI personality. The lexicons are built based on eight MBTI datasets, different features (unigram, 1-2 grams, 1-2-3 grams) and weightings (TF, TF-IDF, TF-logIDF), and different supervised learning models. Then we ran correlation analysis between our MBTI lexicons and other existing lexicons, such as Big-5, emotion, sentiment, age, gender. The correlation analysis shows interesting and reasonable correlation between different personality dimensions and other psychological traits, and it also provides evidence for the robustness of our lexicons.