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Mapping dreams in a computational space: A phrase-level model for analyzing Fight/Flight and other typical situations in dream reports.

Maja Gutman Music, Pavan Holur, Kelly Bulkeley

Consciousness and Cognition October 27, 2022 DOI: 10.1016/j.concog.2022.103428 (opens in new tab)

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AI-extracted from the abstract
Characteristics Computational linguistic analysis Peer reviewed
Population Large collections of dreams
Keywords Humans Dreams Linguistics Semantics Network analysis Representation learning Semantic structure Pattern quantification Fight/flight Flying/falling Typical situation
Key points The authors demonstrate that an automated linguistic system, the Oneirograph, can computationally map typical dream situations in terms of characters, activities, and settings. Analysis of fighting and fleeing dreams provides detailed empirical evidence of underlying semantic structures, and the authors indicate the method can be extended to other typical situations such as flying and falling.

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.

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