Work on personality detection has tended to incorporate psychological
features from different personality models, such as BigFive and MBTI. There are
more than 900 psychological features, each of which is helpful for personality
detection. However, when used in combination, the application of different
calculation standards among these features may result in interference between
features calculated using distinct systems, thereby introducing noise and
reducing performance. This paper adapts different psychological models in the
proposed PsyAttention for personality detection, which can effectively encode
psychological features, reducing their number by 85%. In experiments on the
BigFive and MBTI models, PysAttention achieved average accuracy of 65.66% and
86.30%, respectively, outperforming state-of-the-art methods, indicating that
it is effective at encoding psychological features.

该论文介绍了一种用于个性检测的心理关注模型（PsyAttention），它能够有效编码心理特征，将特征数量减少了 85％。在对 BigFive 和 MBTI 模型进行的实验中，PsyAttention 的平均准确率分别为 65.66％和 86.30％，表现优于现有方法，表明它在编码心理特征方面是有效的。