AWS-EP: A Multi-Task Prediction Approach for MBTI/Big5 Personality Tests
Personality and preferences are essential variables in computational sociology and social science. They describe differences between people at both individual and group levels. In recent years, automated approaches to detect personality traits have received much attention due to the massive availability of individuals' digital footprints. Furthermore, researchers have demonstrated a strong link between personality traits and various downstream tasks such as personalized filtering, profile categorization, and profile embedding. Therefore, the detection of individuals' personality traits has become a critical process for improving the performance of different tasks. In this paper, we build on the importance of the individual personality and propose a novel multitask modeling approach that understands and models the user personality based on its textual posts and comments within a multimedia framework. Experiments and results demonstrate that our model outperforms state-of-the-art performances across multiple famous personality datasets.
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