htmlExploring the Potential of Large Language Models for Text-Based Personality Prediction — Maria Molchanova
Maria Molchanova
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Research Paper

Exploring the Potential of Large Language Models for Text-Based Personality Prediction

29th International Conference on Applications of Natural Language to Information Systems (NLDB 2024)

Springer LNCS · NLDB 20242024

Published in Springer Lecture Notes in Computer Science, vol. 14763, pp. 291–301.

The paper examines whether LLMs can infer personality traits from text. It uses the Big Five framework, with a more detailed experimental focus on extraversion.

The research evaluates prompt-engineering strategies, ways of describing personality traits in instructions, and the effect of prompt wording on classification quality. Results are compared against traditional approaches to text-based personality prediction.

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29th International Conference on Applications of Natural Language to Information Systems

NLDB is an international conference series on NLP and information systems, running since the 1990s. Its proceedings appear in Springer's Lecture Notes in Computer Science (LNCS). The 2024 event was the 29th edition.

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