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

TL;DR

This study explores how the structure of the English free association network influences the solutions to Remote Association Tests, revealing that different difficulty levels are solved by leveraging either strong or moderate associations.

Contribution

It introduces a network-based interpretation of RAT solutions and proposes heuristic algorithms that mimic human search strategies based on association strength.

Findings

Easily solvable RATs rely on strong associations directly connecting words.

Medium and hard RATs are solved by following sequences of moderately weak associations.

The solution process can be modeled as a first passage search on a word association network.

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.