A Language-independent and Compositional Model for Personality Trait Recognition from Short Texts

Fei Liu, Julien Perez, Scott Nowson


Abstract
There have been many attempts at automatically recognising author personality traits from text, typically incorporating linguistic features with conventional machine learning models, e.g. linear regression or Support Vector Machines. In this work, we propose to use deep-learning-based models with atomic features of text – the characters – to build hierarchical, vectorial word and sentence representations for the task of trait inference. On a corpus of tweets, this method shows state-of-the-art performance across five traits and three languages (English, Spanish and Italian) compared with prior work in author profiling. The results, supported by preliminary visualisation work, are encouraging for the ability to detect complex human traits.
Anthology ID:
E17-1071
Volume:
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
Month:
April
Year:
2017
Address:
Valencia, Spain
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
754–764
Language:
URL:
https://www.aclweb.org/anthology/E17-1071
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/E17-1071.pdf