A theory of interpretive clustering in free recall

TL;DR

This paper introduces a stochastic model of short-term verbal memory using a semantic graph, predicting recall phenomena and revealing a novel link between word length and contiguity, confirmed by data analysis.

Contribution

It presents a new probabilistic model of free recall based on semantic graph diffusion, linking word length to recall contiguity effects.

Findings

Shorter words exhibit stronger forward contiguity.

The model predicts well-known recall phenomena.

Archival data confirms the link between word length and contiguity.

Abstract

A stochastic model of short-term verbal memory is proposed, in which the psychological state of the subject is encoded as the instantaneous position of a particle diffusing over a semantic graph with a probabilistic structure. The model is particularly suitable for studying the dependence of free-recall observables on semantic properties of the words to be recalled. Besides predicting some well-known experimental features (contiguity effect, forward asymmetry, word-length effect), a novel prediction is obtained on the relationship between the contiguity effect and the syllabic length of words; shorter words, by way of their wider semantic range, are predicted to be characterized by stronger forward contiguity. A fresh analysis of archival data allows to confirm this prediction.