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Structure in the stream of consciousness: Evidence from a verbalized thought protocol and automated text analytic methods.

Chandra Sripada, Aman Taxali

Consciousness and cognition October 1, 2020 DOI: 10.1016/j.concog.2020.103007 via PubMed

Summary

AI-generated from the abstract

The spontaneous stream of thought (SST), often called the stream of consciousness, exhibits a "clump-and-jump" structure: clusters of related thoughts about a topic followed by a jump to a new topic, in a repeating pattern. Multiple lines of evidence support this structure, including high interrater agreement in identifying jumps, corroboration by automated text analytic methods, identification by a data-driven algorithm, and inferred presence in unverbalized SST. Jumps involve a discontinuous shift where a new clump is only modestly related to the previous one. These results illuminate serial structure in SST and invite research into the processes generating the pattern.

Study at a glance

Characteristics Empirical study using verbalized thought protocol Peer reviewed
Keywords Mind wandering Natural language processing Spontaneous thought Stream of consciousness Text analytics
Key finding The spontaneous stream of thought exhibits a clump-and-jump structure, with clusters of related thoughts followed by jumps to new topics, and jumps involve a discontinuous shift.

Abstract

A key question about the spontaneous stream of thought (SST), often called the stream of consciousness, concerns its serial structure: How are thoughts in an extended sequence related to each other? In this study, we used a verbalized thought protocol to investigate "clump-and-jump" structure in SST-clusters of related thoughts about a topic followed by a jump to a new topic, in a repeating pattern. Several lines of evidence convergently supported the presence of clump-and-jump structure: high interrater agreement in identifying jumps, corroboration of rater-assigned jumps by automated text analytic methods, identification of clumps and jumps by a data-driven algorithm, and the inferred presence of clumps and jumps in unverbalized SST. We also found evidence that jumps involve a discontinuous shift in which a new clump is only modestly related to the previous one. These results illuminate serial structure in SST and invite research into the processes that generate the clump-and-jump pattern.

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