Papers with personality prediction

4 papers
Incorporating Textual Information on User Behavior for Personality Prediction (P19-2)

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Challenge: Recent studies have shown that textual information of user posts and user behaviors are useful for predicting the personality of social media users.
Approach: They propose to use textual information of user behaviors to predict personality of Twitter users by taking user behaviors into account.
Outcome: The proposed models can predict personality of users who do not post frequently, while taking user behaviors into account.
Learning to Answer Psychological Questionnaire for Personality Detection (2021.findings-emnlp)

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Challenge: Existing text-based personality detection research relies on data-driven approaches to implicitly capture personality cues in online posts lacking the guidance of psychological knowledge.
Approach: They propose a model to capture key information in texts and a questionnaire to help the user to make a personality assessment.
Outcome: The proposed model captures key information in texts and a questionnaire and can be used to improve personality prediction.
MBTI Personality Prediction for Fictional Characters Using Movie Scripts (2022.findings-emnlp)

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Challenge: Existing NLP models cannot predict character's personality types based on text classifications . character comprehension is the cornerstone of understanding stories in psychology and education.
Approach: They propose a benchmark to predict movie character's MBTI or Big 5 personality types based on the narratives of the character.
Outcome: The proposed model outperforms existing models in the task and is more accurate than random guesses.
EERPD: Leveraging Emotion and Emotion Regulation for Improving Personality Detection (2025.coling-main)

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Challenge: Existing methods for personality detection ignore the connection between psychological knowledge “emotion regulation” and personality traits.
Approach: They propose to use emotion regulation and emotion features to retrieve few-shot samples and provide process CoTs for inferring labels from text.
Outcome: The proposed method outperforms SOTA by 15.05/4.29 on the two benchmark datasets.

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