Spiritual versus religious: a Natural Language Processing perspective
The method of Natural Language Processing (NLP) is used to analyze the literature on spirituality and religion. Specifically, the corpus produced in the spirituality/religion related scholarly literatures are used to train unsupervised neural network models (Word2Vec) that learn the extent to which...
| Главные авторы: | ; |
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| Формат: | Электронный ресурс Статья |
| Язык: | Английский |
| Проверить наличие: | HBZ Gateway |
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| Fernleihe: | Fernleihe für die Fachinformationsdienste |
| Опубликовано: |
International Association of Management, Spirituality & Religion
2024
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| В: |
Journal of management, spirituality & religion
Год: 2024, Том: 21, Выпуск: 1, Страницы: 63-82 |
| Индексация IxTheo: | AD Социология религии AG Религиозная жизнь ZG Media studies; Digital media; Communication studies |
| Другие ключевые слова: | B
Spirituality
B Религия (мотив) B Stochastic Neighbor Embedding B Natural Language Processing B Word2Vec B Aufsatz in Zeitschrift |
| Online-ссылка: |
Volltext (lizenzpflichtig) |
| Итог: | The method of Natural Language Processing (NLP) is used to analyze the literature on spirituality and religion. Specifically, the corpus produced in the spirituality/religion related scholarly literatures are used to train unsupervised neural network models (Word2Vec) that learn the extent to which words associate syntactically and semantically with one another. These models provide insights into what scholars mean when they use such terms as spiritual, religious, and spiritual-but-not-religious. For instance, they reveal that in the scholarly literature the term spiritual is used more often in contexts that describe an individual's experiences, emotions, and feelings, whereas the term religious is used more often in contexts that highlight an individual's identity and affiliations. The results also suggest that NLP methods may help scholars to perform reasonably meaningful vector operations (e. g., spiritual minus religious) that can be used to explore quickly and efficiently the syntactic and semantic patterns in a large corpus. |
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| ISSN: | 1942-258X |
| Второстепенные работы: | Enthalten in: Journal of management, spirituality & religion
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| Persistent identifiers: | DOI: 10.51327/TUFP3116 |