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arXiv · 1711.09824

Lexical-semantic resources: yet powerful resources for automatic personality classification

Xuan-Son Vu·Lucie Flekova·Lili Jiang·Iryna Gurevych
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Abstract

In this paper, we aim to reveal the impact of lexical-semantic resources, used in particular for word sense disambiguation and sense-level semantic categorization, on automatic personality classification task. While stylistic features (e.g., part-of-speech counts) have been shown their power in this task, the impact of semantics beyond targeted word lists is relatively unexplored. We propose and extract three types of lexical-semantic features, which capture high-level concepts and emotions, overcoming the lexical gap of word n-grams. Our experimental results are comparable to state-of-the-art methods, while no personality-specific resources are required.

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Xuan-Son Vu, Lucie Flekova, Lili Jiang, Iryna Gurevych. 2017-11-27. Lexical-semantic resources: yet powerful resources for automatic personality classification. https://arxiv.org/abs/1711.09824

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