The Cognitive Social Network in Dreams: Transitivity, Assortativity, and Giant Component Proportion Are Monotonic

Area of Science:

• Cognitive Psychology
• Social Network Analysis
• Dream Research

Background:

• Social networks in waking life exhibit specific structural properties.
• Dream content often involves social interactions, but its network structure is less understood.
• Understanding dream network structure may reveal insights into cognitive processes.

Purpose of the Study:

• To construct and analyze social networks derived from individuals' dreams.
• To investigate the structural properties of dream social networks, specifically transitivity, assortativity, and giant component proportion.
• To compare dream social network structures with those of waking life and online social networks.

Main Methods:

• Social networks were created from dream reports of five individuals.
• Key network metrics including transitivity, assortativity, and giant component proportion were calculated.
• Statistical analysis explored monotonic relationships between these network measures.

Main Results:

• A monotonic relationship was observed: as transitivity increased, assortativity increased and giant component proportion decreased across the five dream networks.
• Dream social networks exhibited negative or near-zero assortativity, contrasting with the positive assortativity typical of waking life networks.
• A random walk model, particularly with biased associations, could replicate the observed negative assortativity in dream networks.

Conclusions:

• Characters appear systematically in dreams, reflecting the dreamer's cognitive social network.
• Dream social networks are not direct replicas of cognitive social networks, possessing distinct structural characteristics.
• The findings suggest cognitive processes, potentially involving biased random walks, shape dream social network formation.