TY - JOUR
T1 - The semantic distance task
T2 - Quantifying semantic distance with semantic network path length
AU - Kenett, Yoed N.
AU - Levi, Effi
AU - Anaki, David
AU - Faust, Miriam
N1 - Publisher Copyright:
© 2017 American Psychological Association.
PY - 2017/9
Y1 - 2017/9
N2 - Semantic distance is a determining factor in cognitive processes, such as semantic priming, operating upon semantic memory. The main computational approach to compute semantic distance is through latent semantic analysis (LSA). However, objections have been raised against this approach, mainly in its failure at predicting semantic priming. We propose a novel approach to computing semantic distance, based on network science methodology. Path length in a semantic network represents the amount of steps needed to traverse from 1 word in the network to the other. We examine whether path length can be used as a measure of semantic distance, by investigating how path length affect performance in a semantic relatedness judgment task and recall from memory. Our results show a differential effect on performance: Up to 4 steps separating between word-pairs, participants exhibit an increase in reaction time (RT) and decrease in the percentage of word-pairs judged as related. From 4 steps onward, participants exhibit a significant decrease in RT and the word-pairs are dominantly judged as unrelated. Furthermore, we show that as path length between word-pairs increases, success in free- and cued-recall decreases. Finally, we demonstrate how our measure outperforms computational methods measuring semantic distance (LSA and positive pointwise mutual information) in predicting participants RT and subjective judgments of semantic strength. Thus, we provide a computational alternative to computing semantic distance. Furthermore, this approach addresses key issues in cognitive theory, namely the breadth of the spreading activation process and the effect of semantic distance on memory retrieval.
AB - Semantic distance is a determining factor in cognitive processes, such as semantic priming, operating upon semantic memory. The main computational approach to compute semantic distance is through latent semantic analysis (LSA). However, objections have been raised against this approach, mainly in its failure at predicting semantic priming. We propose a novel approach to computing semantic distance, based on network science methodology. Path length in a semantic network represents the amount of steps needed to traverse from 1 word in the network to the other. We examine whether path length can be used as a measure of semantic distance, by investigating how path length affect performance in a semantic relatedness judgment task and recall from memory. Our results show a differential effect on performance: Up to 4 steps separating between word-pairs, participants exhibit an increase in reaction time (RT) and decrease in the percentage of word-pairs judged as related. From 4 steps onward, participants exhibit a significant decrease in RT and the word-pairs are dominantly judged as unrelated. Furthermore, we show that as path length between word-pairs increases, success in free- and cued-recall decreases. Finally, we demonstrate how our measure outperforms computational methods measuring semantic distance (LSA and positive pointwise mutual information) in predicting participants RT and subjective judgments of semantic strength. Thus, we provide a computational alternative to computing semantic distance. Furthermore, this approach addresses key issues in cognitive theory, namely the breadth of the spreading activation process and the effect of semantic distance on memory retrieval.
KW - LSA
KW - Memory recall
KW - Network science
KW - Semantic distance
KW - Spreading activation
UR - http://www.scopus.com/inward/record.url?scp=85013787277&partnerID=8YFLogxK
U2 - 10.1037/xlm0000391
DO - 10.1037/xlm0000391
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C2 - 28240936
SN - 0278-7393
VL - 43
SP - 1470
EP - 1489
JO - Journal of Experimental Psychology: Learning Memory and Cognition
JF - Journal of Experimental Psychology: Learning Memory and Cognition
IS - 9
ER -