Lexical-semantic resources: yet powerful resources for automatic personality classification
Computation and Language
2017-11-28 v1
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.
Cite
@article{arxiv.1711.09824,
title = {Lexical-semantic resources: yet powerful resources for automatic personality classification},
author = {Xuan-Son Vu and Lucie Flekova and Lili Jiang and Iryna Gurevych},
journal= {arXiv preprint arXiv:1711.09824},
year = {2017}
}