Automatic Estimation of Multidimensional Personality From a Single Sound-Symbolic Word
Researchers typically use the “big five” traits (Extroversion, Agreeableness, Conscientiousness, Neuroticism, and Openness) as a standard way to describe personality. Evaluation of personality is generally conducted using self-report questionnaires that require participants to respond to a large num...
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Format: | Article |
Language: | English |
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Frontiers Media S.A.
2021-04-01
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Series: | Frontiers in Psychology |
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Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyg.2021.595986/full |
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author | Maki Sakamoto Junji Watanabe Koichi Yamagata |
author_facet | Maki Sakamoto Junji Watanabe Koichi Yamagata |
author_sort | Maki Sakamoto |
collection | DOAJ |
description | Researchers typically use the “big five” traits (Extroversion, Agreeableness, Conscientiousness, Neuroticism, and Openness) as a standard way to describe personality. Evaluation of personality is generally conducted using self-report questionnaires that require participants to respond to a large number of test items. To minimize the burden on participants, this paper proposes an alternative method of estimating multidimensional personality traits from only a single word. We constructed a system that can convert a sound-symbolic word (SSW) that intuitively expresses personality traits into information expressed by 50 personality-related adjective pairs. This system can obtain information equivalent to the adjective scales using only a single word instead of asking many direct questions. To achieve this, we focused on SSWs in Japanese that have the association between linguistic sounds and meanings and express diverse and complex aspects of personality traits. We evaluated the prediction accuracy of the system and found that the multiple correlation coefficients for 48 personality-related adjective pairs exceeded 0.75, indicating that the model could explain more than half of the variations in the data. In addition, we conducted an evaluation experiment in which participants rated the appropriateness of the system output using a seven-point scale (with −3 as absolutely inappropriate and +3 as completely appropriate). The average score for 50 personality-related adjective pairs was 1.25. Thus, we believe that this system can contribute to the field of personality computing, particularly in terms of personality evaluation and communication. |
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format | Article |
id | doaj.art-b966fc3ba4de44aebc59d3bdd3e53b5d |
institution | Directory Open Access Journal |
issn | 1664-1078 |
language | English |
last_indexed | 2024-12-13T15:23:48Z |
publishDate | 2021-04-01 |
publisher | Frontiers Media S.A. |
record_format | Article |
series | Frontiers in Psychology |
spelling | doaj.art-b966fc3ba4de44aebc59d3bdd3e53b5d2022-12-21T23:40:28ZengFrontiers Media S.A.Frontiers in Psychology1664-10782021-04-011210.3389/fpsyg.2021.595986595986Automatic Estimation of Multidimensional Personality From a Single Sound-Symbolic WordMaki Sakamoto0Junji Watanabe1Koichi Yamagata2Department of Informatics, The University of Electro-Communications, Chofu, JapanNTT Communication Science Laboratories, Nippon Telegraph and Telephone Corporation, Atsugi, JapanDepartment of Informatics, The University of Electro-Communications, Chofu, JapanResearchers typically use the “big five” traits (Extroversion, Agreeableness, Conscientiousness, Neuroticism, and Openness) as a standard way to describe personality. Evaluation of personality is generally conducted using self-report questionnaires that require participants to respond to a large number of test items. To minimize the burden on participants, this paper proposes an alternative method of estimating multidimensional personality traits from only a single word. We constructed a system that can convert a sound-symbolic word (SSW) that intuitively expresses personality traits into information expressed by 50 personality-related adjective pairs. This system can obtain information equivalent to the adjective scales using only a single word instead of asking many direct questions. To achieve this, we focused on SSWs in Japanese that have the association between linguistic sounds and meanings and express diverse and complex aspects of personality traits. We evaluated the prediction accuracy of the system and found that the multiple correlation coefficients for 48 personality-related adjective pairs exceeded 0.75, indicating that the model could explain more than half of the variations in the data. In addition, we conducted an evaluation experiment in which participants rated the appropriateness of the system output using a seven-point scale (with −3 as absolutely inappropriate and +3 as completely appropriate). The average score for 50 personality-related adjective pairs was 1.25. Thus, we believe that this system can contribute to the field of personality computing, particularly in terms of personality evaluation and communication.https://www.frontiersin.org/articles/10.3389/fpsyg.2021.595986/fullpersonality evaluationsystem constructionsound-symbolic wordonomatopoeiaJapanese |
spellingShingle | Maki Sakamoto Junji Watanabe Koichi Yamagata Automatic Estimation of Multidimensional Personality From a Single Sound-Symbolic Word Frontiers in Psychology personality evaluation system construction sound-symbolic word onomatopoeia Japanese |
title | Automatic Estimation of Multidimensional Personality From a Single Sound-Symbolic Word |
title_full | Automatic Estimation of Multidimensional Personality From a Single Sound-Symbolic Word |
title_fullStr | Automatic Estimation of Multidimensional Personality From a Single Sound-Symbolic Word |
title_full_unstemmed | Automatic Estimation of Multidimensional Personality From a Single Sound-Symbolic Word |
title_short | Automatic Estimation of Multidimensional Personality From a Single Sound-Symbolic Word |
title_sort | automatic estimation of multidimensional personality from a single sound symbolic word |
topic | personality evaluation system construction sound-symbolic word onomatopoeia Japanese |
url | https://www.frontiersin.org/articles/10.3389/fpsyg.2021.595986/full |
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