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Query: "author" (Maja Gutman Mušič) .

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1.
The last sanctum of archetypes : rethinking dreams in the light of ancient knowledge and artificial intelligence
Maja Gutman Mušič, 2023, original scientific article

Abstract: Despite numerous attempts to integrate dream research into a vast array of sci-entific disciplines, there appears to be no consensus on why and how we dream. This millennia-old universal human phenomenon appears to be too elusive to be thoroughly understood by a single scientific discipline and too complex and data--rich to be studied only theoretically. However, another dimension to dreams and dreaming could promise an integrative approach: the culture-historical compo-nent that merges with recent advances in artificial Intelligence. This paper briefly examines conceptual understandings of dreams before the dawn of modern science – specifically, the Native american, Mesopotamian, ancient Greek, and Hippocra-tic principles of dream practices and knowledge – in an attempt to understand the contemporary dream research field better and to outline future avenues for a data-driven approach while remaining grounded in its epistemological foundation.
Keywords: ancient dreaming, archetypes, artificial intelligence, dream data, cross-cultural dream analysis
Published in DiRROS: 13.05.2024; Views: 82; Downloads: 73
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2.
Mapping dreams in a computational space : a phrase-level model for analyzing Fight/Flight and other typical situations in dream reports
Maja Gutman Mušič, Pavan Holur, Kelly Bulkeley, 2022, original scientific article

Abstract: This article demonstrates that an automated system of linguistic analysis can be developed – the Oneirograph – to analyze large collections of dreams and computationally map their contents in terms of typical situations involving an interplay of characters, activities, and settings. Focusing the analysis first on the twin situations of fighting and fleeing, the results provide densely detailed empirical evidence of the underlying semantic structures of typical dreams. The results also indicate that the Oneirograph analytic system can be applied to other typical dream situations as well (e.g., flying, falling), each of which can be computationally mapped in terms of a distinctive constellation of characters, activities, and settings.
Keywords: dreams, patterns, natural language processing, Oneirograph, network analysis, semantic structure
Published in DiRROS: 22.03.2023; Views: 411; Downloads: 228
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