Exploring the dynamics of Shannon’s information and iconicity in language processing and lexeme evolution

This two-part meta-study explores the relationship of Shannon's information and iconicity in American English, with a focus on their implications for cognitive processing and the evolution of lexemes. Part one explores the expression of information in iconic words by calculating phonemic bigram surprisal using a very large corpus of spoken American English and cross referencing it with iconicity ratings. Iconic words-those with a form/meaning resemblance-are known to be processed with a cognitive advantage, so they are included in our tests as a benchmark. Within the framework of the Iconic Treadmill Hypothesis, we posit that as iconic words evolve towards arbitrariness, bigram sequences become more predictable, offsetting some the cognitive costs associated with processing arbitrary words. In part 2, we extend Cognitive Load Theory and the Lossy Context Surprisal Model-both sentence level language processing models-to test our predictions at the bigram level using the results of a battery of existing psycholinguistic experiments. In line with these models that explain the psycholinguistic consequences of hearing improbable words in sentences, our results show that words made up of improbable phonemes are processed with cognitive disadvantage, but that extra processing effort enhances their retention in long term memory. Overall, our findings speak to the cognitive limitations of language processing and how these limitations influence lexeme evolution.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2025-04-29
DOI
https://doi.org/10.1371/journal.pone.0321294
Citations
3
Primary Topic
Multisensory perception and integration
Type
article
Field-Weighted Citation Impact
6.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring the dynamics of Shannon’s information and iconicity in language processing and lexeme evolution

Rikke L. Bundgaard-Nielsen, Alexander Kilpatrick
3 citations
PLoS ONE
Multisensory perception and integration
6.35
article

Exploring the dynamics of Shannon’s information and iconicity in language processing and lexeme evolution

Rikke L. Bundgaard-Nielsen, Alexander Kilpatrick
article en
3 citations

Abstract

This two-part meta-study explores the relationship of Shannon's information and iconicity in American English, with a focus on their implications for cognitive processing and the evolution of lexemes. Part one explores the expression of information in iconic words by calculating phonemic bigram surprisal using a very large corpus of spoken American English and cross referencing it with iconicity ratings. Iconic words-those with a form/meaning resemblance-are known to be processed with a cognitive advantage, so they are included in our tests as a benchmark. Within the framework of the Iconic Treadmill Hypothesis, we posit that as iconic words evolve towards arbitrariness, bigram sequences become more predictable, offsetting some the cognitive costs associated with processing arbitrary words. In part 2, we extend Cognitive Load Theory and the Lossy Context Surprisal Model-both sentence level language processing models-to test our predictions at the bigram level using the results of a battery of existing psycholinguistic experiments. In line with these models that explain the psycholinguistic consequences of hearing improbable words in sentences, our results show that words made up of improbable phonemes are processed with cognitive disadvantage, but that extra processing effort enhances their retention in long term memory. Overall, our findings speak to the cognitive limitations of language processing and how these limitations influence lexeme evolution.

PLoS ONEVol. 20(4)
University of Aizu (JP), The University of Melbourne (AU)
Japan Society for the Promotion of Science London
Quality Education
Openalex Percentile: Top 4%
Multisensory perception and integration
6.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.