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Cognitive modelling with multilayer networks: Insights, advancements and future challenges
Cognitive multilayer networks can map multiple types of information at once, thus capturing how different layers of associations might co-exist within the mental lexicon and influence cognitive processing.
Feature-rich multiplex lexical networks reveal mental strategies of early language learning
Modelling words as vectors is key to natural language processing, whereas networks of word associations can map the nature of semantic memory.
Cognitive networks identify the content of English and Italian popular posts about COVID-19 vaccines: Anticipation, logistics, conspiracy and loss of trust
Semantic associations with "vaccine," "hoax" and conspiratorial jargon indicated the persistence of conspiracy theories and vaccines in massively read English posts (absent in Italian messages).
The origins of Zipf's meaning-frequency law
In his pioneering research, G. K. Zipf observed that more frequent words tend to have more meanings, and showed that the number of meanings of a word grows as the square root of its frequency.
