Personality Recognition from Source Code Based on Lexical, Syntactic and Semantic Features

Automatic personality recognition from source code is a scarcely explored problem. We propose personality recognition with handcrafted features, based on lexical, syntactic and semantic properties of source code. Out of 35 proposed features, 22 features are completely novel. We also show that n-gram...

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Detalles Bibliográficos
Autores principales: Biel, Mikołaj, Kuta, Marcin, Kitowski, Jacek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302843/
http://dx.doi.org/10.1007/978-3-030-50417-5_26
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author Biel, Mikołaj
Kuta, Marcin
Kitowski, Jacek
author_facet Biel, Mikołaj
Kuta, Marcin
Kitowski, Jacek
author_sort Biel, Mikołaj
collection PubMed
description Automatic personality recognition from source code is a scarcely explored problem. We propose personality recognition with handcrafted features, based on lexical, syntactic and semantic properties of source code. Out of 35 proposed features, 22 features are completely novel. We also show that n-gram features are simple but surprisingly good predictors of personality and present results arising from joint usage of both handcrafted and baseline features. Additionally we compare our results with scores obtained within the Personality Recognition in SOurce COde track during Forum for Information Retrieval Evaluation 2016 and set up state-of-the-art results for conscientiousness and neuroticism traits.
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spelling pubmed-73028432020-06-19 Personality Recognition from Source Code Based on Lexical, Syntactic and Semantic Features Biel, Mikołaj Kuta, Marcin Kitowski, Jacek Computational Science – ICCS 2020 Article Automatic personality recognition from source code is a scarcely explored problem. We propose personality recognition with handcrafted features, based on lexical, syntactic and semantic properties of source code. Out of 35 proposed features, 22 features are completely novel. We also show that n-gram features are simple but surprisingly good predictors of personality and present results arising from joint usage of both handcrafted and baseline features. Additionally we compare our results with scores obtained within the Personality Recognition in SOurce COde track during Forum for Information Retrieval Evaluation 2016 and set up state-of-the-art results for conscientiousness and neuroticism traits. 2020-06-15 /pmc/articles/PMC7302843/ http://dx.doi.org/10.1007/978-3-030-50417-5_26 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Biel, Mikołaj
Kuta, Marcin
Kitowski, Jacek
Personality Recognition from Source Code Based on Lexical, Syntactic and Semantic Features
title Personality Recognition from Source Code Based on Lexical, Syntactic and Semantic Features
title_full Personality Recognition from Source Code Based on Lexical, Syntactic and Semantic Features
title_fullStr Personality Recognition from Source Code Based on Lexical, Syntactic and Semantic Features
title_full_unstemmed Personality Recognition from Source Code Based on Lexical, Syntactic and Semantic Features
title_short Personality Recognition from Source Code Based on Lexical, Syntactic and Semantic Features
title_sort personality recognition from source code based on lexical, syntactic and semantic features
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302843/
http://dx.doi.org/10.1007/978-3-030-50417-5_26
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AT kutamarcin personalityrecognitionfromsourcecodebasedonlexicalsyntacticandsemanticfeatures
AT kitowskijacek personalityrecognitionfromsourcecodebasedonlexicalsyntacticandsemanticfeatures

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