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Semantic diversity:A measure of contextual variation in word meaning based on latent semantic analysis
Authors
AM Woollams
British National Corpus Consortium
+53 more
C Metzler
CD Piercey
D Kieras
DA Cruse
DE Klein
E Jefferies
E Jefferies
EM Saffran
F Corbett
G Kellas
GA Miller
H Head
H Rubenstein
J Altarriba
J Morton
J Rodd
JD Bransford
JE Jastrzembski
JL Elman
JL McClelland
JM Rodd
JM Rodd
JM Rodd
JS Adelman
JT Giles
K Lund
KA Noonan
M Bedny
M Coltheart
MA Lambon Ralph
Matthew A. Lambon Ralph
MF St. John
MJ Yap
MN Jones
MW Harm
P Hoffman
P Hoffman
P Hoffman
Paul Hoffman
PJ Schwanenflugel
PJ Schwanenflugel
R Borowsky
RC Galbraith
S Zeno
SA McDonald
Timothy T. Rogers
TK Landauer
TK Landauer
TL Griffiths
TT Rogers
TT Rogers
Y Hino
Y Hino
Publication date
1 September 2013
Publisher
'Springer Science and Business Media LLC'
Doi
Cite
Abstract
Semantic ambiguity is typically measured by summing the number of senses or dictionary definitions that a word has. Such measures are somewhat subjective and may not adequately capture the full extent of variation in word meaning, particularly for polysemous words that can be used in many different ways, with subtle shifts in meaning. Here, we describe an alternative, computationally derived measure of ambiguity based on the proposal that the meanings of words vary continuously as a function of their contexts. On this view, words that appear in a wide range of contexts on diverse topics are more variable in meaning than those that appear in a restricted set of similar contexts. To quantify this variation, we performed latent semantic analysis on a large text corpus to estimate the semantic similarities of different linguistic contexts. From these estimates, we calculated the degree to which the different contexts associated with a given word vary in their meanings. We term this quantity a word's semantic diversity (SemD). We suggest that this approach provides an objective way of quantifying the subtle, context-dependent variations in word meaning that are often present in language. We demonstrate that SemD is correlated with other measures of ambiguity and contextual variability, as well as with frequency and imageability. We also show that SemD is a strong predictor of performance in semantic judgments in healthy individuals and in patients with semantic deficits, accounting for unique variance beyond that of other predictors. SemD values for over 30,000 English words are provided as supplementary materials. © 2012 Psychonomic Society, Inc
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The University of Manchester - Institutional Repository
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