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1.
Clustering and blockmodeling temporal networks - two indirect approaches
Vladimir Batagelj, 2023, objavljeni znanstveni prispevek na konferenci

Povzetek: Two approaches to clustering and blockmodeling of temporal networks are presented: the first is based on an adaptation of the clustering of symbolic data described by modal values and the second is based on clustering with relational constraints. Different options for describing a temporal block model are discussed.
Ključne besede: social networks, network analysis, blockmodeling, symbolic data analysis, clustering with relational constraints
Objavljeno v DiRROS: 08.04.2024; Ogledov: 82; Prenosov: 41
.pdf Celotno besedilo (461,70 KB)
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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, Pavan Holur, Kelly Bulkeley, 2022, izvirni znanstveni članek

Povzetek: 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.
Ključne besede: dreams, patterns, natural language processing, Oneirograph, network analysis, semantic structure
Objavljeno v DiRROS: 22.03.2023; Ogledov: 351; Prenosov: 203
.pdf Celotno besedilo (3,74 MB)
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