New Approach of Measuring Human Personality Traits Using Ontology-Based Model from Social Media Data
Human online activities leave digital traces that provide a perfect opportunity to understand their behavior better. Social media is an excellent place to spark conversations or state opinions. Thus, it generates large-scale textual data. In this paper, we harness those data to support the effort of...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/12/10/413 |
| _version_ | 1797514307867508736 |
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| author | Andry Alamsyah Nidya Dudija Sri Widiyanesti |
| author_facet | Andry Alamsyah Nidya Dudija Sri Widiyanesti |
| author_sort | Andry Alamsyah |
| collection | DOAJ |
| description | Human online activities leave digital traces that provide a perfect opportunity to understand their behavior better. Social media is an excellent place to spark conversations or state opinions. Thus, it generates large-scale textual data. In this paper, we harness those data to support the effort of personality measurement. Our first contribution is to develop the Big Five personality trait-based model to detect human personalities from their textual data in the Indonesian language. The model uses an ontology approach instead of the more famous machine learning model. The former better captures the meaning and intention of phrases and words in the domain of human personality. The legacy and more thorough ways to assess nature are by doing interviews or by giving questionnaires. Still, there are many real-life applications where we need to possess an alternative method, which is cheaper and faster than the legacy methodology to select individuals based on their personality. The second contribution is to support the model implementation by building a personality measurement platform. We use two distinct features for the model: an n-gram sorting algorithm to parse the textual data and a crowdsourcing mechanism that facilitates public involvement contributing to the ontology corpus addition and filtering. |
| first_indexed | 2024-03-10T06:30:06Z |
| format | Article |
| id | doaj.art-c6d90709b33c4318821776a1dbc77695 |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-10T06:30:06Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-c6d90709b33c4318821776a1dbc776952023-11-22T18:37:46ZengMDPI AGInformation2078-24892021-10-01121041310.3390/info12100413New Approach of Measuring Human Personality Traits Using Ontology-Based Model from Social Media DataAndry Alamsyah0Nidya Dudija1Sri Widiyanesti2School of Economics and Business, Telkom University, Bandung 40257, IndonesiaSchool of Economics and Business, Telkom University, Bandung 40257, IndonesiaSchool of Economics and Business, Telkom University, Bandung 40257, IndonesiaHuman online activities leave digital traces that provide a perfect opportunity to understand their behavior better. Social media is an excellent place to spark conversations or state opinions. Thus, it generates large-scale textual data. In this paper, we harness those data to support the effort of personality measurement. Our first contribution is to develop the Big Five personality trait-based model to detect human personalities from their textual data in the Indonesian language. The model uses an ontology approach instead of the more famous machine learning model. The former better captures the meaning and intention of phrases and words in the domain of human personality. The legacy and more thorough ways to assess nature are by doing interviews or by giving questionnaires. Still, there are many real-life applications where we need to possess an alternative method, which is cheaper and faster than the legacy methodology to select individuals based on their personality. The second contribution is to support the model implementation by building a personality measurement platform. We use two distinct features for the model: an n-gram sorting algorithm to parse the textual data and a crowdsourcing mechanism that facilitates public involvement contributing to the ontology corpus addition and filtering.https://www.mdpi.com/2078-2489/12/10/413personality measurement modelsocial mediaontology modelbig five personality trait |
| spellingShingle | Andry Alamsyah Nidya Dudija Sri Widiyanesti New Approach of Measuring Human Personality Traits Using Ontology-Based Model from Social Media Data Information personality measurement model social media ontology model big five personality trait |
| title | New Approach of Measuring Human Personality Traits Using Ontology-Based Model from Social Media Data |
| title_full | New Approach of Measuring Human Personality Traits Using Ontology-Based Model from Social Media Data |
| title_fullStr | New Approach of Measuring Human Personality Traits Using Ontology-Based Model from Social Media Data |
| title_full_unstemmed | New Approach of Measuring Human Personality Traits Using Ontology-Based Model from Social Media Data |
| title_short | New Approach of Measuring Human Personality Traits Using Ontology-Based Model from Social Media Data |
| title_sort | new approach of measuring human personality traits using ontology based model from social media data |
| topic | personality measurement model social media ontology model big five personality trait |
| url | https://www.mdpi.com/2078-2489/12/10/413 |
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