Analysis of English free association network reveals mechanisms of efficient solution of Remote Association Tests

Olga Valba, Alexander Gorsky, Sergei Nechaev and Mikhail Tamm

PLOS ONE, 2021, vol. 16, issue 4, 1-15

Abstract: We study correlations between the structure and properties of a free association network of the English language, and solutions of psycholinguistic Remote Association Tests (RATs). We show that average hardness of individual RATs is largely determined by relative positions of test words (stimuli and response) on the free association network. We argue that the solution of RATs can be interpreted as a first passage search problem on a network whose vertices are words and links are associations between words. We propose different heuristic search algorithms and demonstrate that in “easily-solving” RATs (those that are solved in 15 seconds by more than 64% subjects) the solution is governed by “strong” network links (i.e. strong associations) directly connecting stimuli and response, and thus the efficient strategy consist in activating such strong links. In turn, the most efficient mechanism of solving medium and hard RATs consists of preferentially following sequence of “moderately weak” associations.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0248986

DOI: 10.1371/journal.pone.0248986

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