Multilingual Transformer-Based Personality Traits Estimation

Autor: Maurizio Morisio, Diego Monti, Giuseppe Rizzo, Simone Leonardi
Rok vydání: 2020
Předmět:
Computer science
media_common.quotation_subject
Empathy
02 engineering and technology
computer.software_genre
Big 5
NLP
Intelligent agent
020204 information systems
0202 electrical engineering
electronic engineering
information engineering
NLP
Affective Computing
Personality Traits
Sentence Embedding
Linguisitc Models
Multilingual Embeddings
Social media
natural language processing
Polysemy
Big Five personality traits
Affective computing
Transformer (machine learning model)
media_common
Personality Traits
lcsh:T58.5-58.64
lcsh:Information technology
business.industry
Deep learning
deep learning
Sentence Embedding
Linguisitc Models
sentence embeddings
Multilingual Embeddings
Affective Computing
020201 artificial intelligence & image processing
Artificial intelligence
business
computer
personality dimensions
Natural language processing
Information Systems
Zdroj: Information
Volume 11
Issue 4
Information, Vol 11, Iss 4, p 179 (2020)
ISSN: 2078-2489
Popis: Intelligent agents have the potential to understand personality traits of human beings because of their every day interaction with us. The assessment of our psychological traits is a useful tool when we require them to simulate empathy. Since the creation of social media platforms, numerous studies dealt with measuring personality traits by gathering users&rsquo
information from their social media profiles. Real world applications showed how natural language processing combined with supervised machine learning algorithms are effective in this field. These applications have some limitations such as focusing on English text only and not considering polysemy in text. In this paper, we propose a multilingual model that handles polysemy by analyzing sentences as a semantic ensemble of interconnected words. The proposed approach processes Facebook posts from the myPersonality dataset and it turns them into a high-dimensional array of features, which are then exploited by a deep neural network architecture based on transformer to perform regression. We prove the effectiveness of our work by comparing the mean squared error of our model with existing baselines and the Kullback&ndash
Leibler divergence between the relative data distributions. We obtained state-of-the-art results in personality traits estimation from social media posts for all five personality traits.
Databáze: OpenAIRE
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