Moral moundations of spirituality and religion through Natural Language Processing
To explore the similarities/differences between the moral contexts in which scholars use the terms religion and spirituality, we use Moral Foundations Dictionary for Linguistic Analyses 2.0 (MFD), a dictionary developed to assess the moral content of text, and a Natural Language Processing algorithm...
| Authors: | ; |
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| 格式: | 電子 Article |
| 語言: | English |
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| Fernleihe: | Fernleihe für die Fachinformationsdienste |
| 出版: |
International Association of Management, Spirituality & Religion
2024
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| In: |
Journal of management, spirituality & religion
Year: 2024, 卷: 21, 發布: 2, Pages: 184-205 |
| Further subjects: | B
Word2vec
B Spirituality B Moral Foundations Theory B Natural Language Processing B Aufsatz in Zeitschrift B 宗教 |
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Volltext (lizenzpflichtig) |
| 總結: | To explore the similarities/differences between the moral contexts in which scholars use the terms religion and spirituality, we use Moral Foundations Dictionary for Linguistic Analyses 2.0 (MFD), a dictionary developed to assess the moral content of text, and a Natural Language Processing algorithm (Word2Vec) that learns the semantic relationships in a corpus. The findings suggest that, except in the virtue words category of the Care foundation dictionary, religion semantically overlaps with a greater percentage of MFD words than does spirituality. Both religion and spirituality have greater semantic overlaps with virtue words than vice words; compared to religion, spirituality's semantic overlaps with vice words are smaller. Spirituality has greater overlaps only with the MFD words for Care and Sanctity; religion has greater semantic overlaps with words for all foundations, particularly the "binding" foundations: Loyalty, Authority, and Sanctity. Similarities notwithstanding, the moral contexts of religion and spirituality feature different aspects of morality. |
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| ISSN: | 1942-258X |
| Contains: | Enthalten in: Journal of management, spirituality & religion
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| Persistent identifiers: | DOI: 10.51327/WLON1757 |