ArticleFrontiers in psychology2013
Community structure in the phonological network.
Article in Frontiers in psychology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Open-access network science: Investigating phonological similarity networks based on the SUBTLEX-US lexicon.Behavior research methods · 2025Article
- Cognitive modelling of concepts in the mental lexicon with multilayer networks: Insights, advancements, and future challenges.Psychonomic bulletin & review · 2024Review
- Obsolescence effects in second language phonological networks.Memory & cognition · 2024Article
- Multiple sclerosis is associated with differences in semantic memory structure.Neuropsychology · 2024Article
- Aesthetic emotions are affected by context: a psychometric network analysis.Scientific reports · 2023Article
- Article
- Semantic Memory and Creativity: The Costs and Benefits of Semantic Memory Structure in Generating Original Ideas.Thinking & reasoning · 2023Article
- Identifying the phonological backbone in the mental lexicon.PloS one · 2023Article
- Database of word-level statistics for Mandarin Chinese (DoWLS-MAN).Behavior research methods · 2022Article
- What Can Network Science Tell Us About Phonology and Language Processing?Topics in cognitive science · 2022Article
- The Challenge of Achieving Greater Generalization in Phonological Treatment of Aphasia.Aphasiology · 2022Article
- Article
- Quantifying flexibility in thought: The resiliency of semantic networks differs across the lifespan.Cognition · 2021Article
- Exploring Networks of Lexical Variation in Russian Sign Language.Frontiers in psychology · 2021Article
- Using Network Science to Map What Montréal Bilinguals Talk about Across Languages and Communicative Contexts.Journal of neurolinguistics · 2020Article
- Phonological network fluency identifies phonological restructuring through mental search.Scientific reports · 2019Article
- Knowledge gaps in the early growth of semantic feature networks.Nature human behaviour · 2018Article
- Multiplex model of mental lexicon reveals explosive learning in humans.Scientific reports · 2018Article
- Orthographic Networks in the Developing Mental Lexicon. Insights From Graph Theory and Implications for the Study of Language Processing.Frontiers in psychology · 2018Article
- The orthographic similarity structure of English words: Insights from network science.Applied network science · 2018Article
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Abstract
Community structure, which refers to the presence of densely connected groups within a larger network, is a common feature of several real-world networks from a variety of domains such as the human brain, social networks of hunter-gatherers and business organizations, and the World Wide Web (Porter et al., 2009). Using a community detection technique known as the Louvain optimization method, 17 communities were extracted from the giant component of the phonological network described in Vitevitch (2008). Additional analyses comparing the lexical and phonological characteristics of words in these communities against words in randomly generated communities revealed several novel discoveries. Larger communities tend to consist of short, frequent words of high degree and low age of acquisition ratings, and smaller communities tend to consist of longer, less frequent words of low degree and high age of acquisition ratings. Real communities also contained fewer different phonological segments compared to random communities, although the number of occurrences of phonological segments found in real communities was much higher than that of the same phonological segments in random communities. Interestingly, the observation that relatively few biphones occur very frequently and a large number of biphones occur rarely within communities mirrors the pattern of the overall frequency of words in a language (Zipf, 1935). The present findings have important implications for understanding the dynamics of activation spread among words in the phonological network that are relevant to lexical processing, as well as understanding the mechanisms that underlie language acquisition and the evolution of language.
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