Accounting for item-level variance in recognition memory: Comparing word frequency and contextual diversity

Johns, Brendan T.

doi:10.3758/s13421-021-01249-z

Cited by 9 publications

(24 citation statements)

References 102 publications

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“…Previous studies have demonstrated the superiority of contextual diversity measures of lexical strength over the classic word frequency measure (Adelman et al, 2006; Johns, 2021a, 2021c; Johns et al, 2020). The goal of this study was to determine if these findings extend to multiword expressions, through the analysis of idiom familiarity values from Libben and Titone (2008).…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, Johns (2021a) has recently demonstrated that the advantage of discourse and user contextual diversity measures generalizes to accounting for word-level recognition memory rates, while Johns (2021c) showed that a distributional model trained with the communication patterns of users on Reddit allowed for a unique signal of word meaning to be constructed. For example, distributional models trained with word-based contextual representations appeared to extract subordinate semantic category members as nearest neighbors of a word (e.g., different dog breeds for poodle , different sports for basketball ).…”

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confidence: 99%

“…By contrast, models encoding users' communication patterns populated a word's semantic neighborhood with properties of that word (e.g., grooming and matting for poodle, rebounds and athleticism for basketball). Combined, the work of Johns (2021aJohns ( , 2021bJohns ( , 2021c suggests that communicative information is an integral part of lexical representations across a number of domains.…”

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Determining the importance of frequency and contextual diversity in the lexical organization of multiword expressions.

Senaldi¹,

Titone²,

Johns³

2022

Canadian Journal of Experimental Psychology / Revue canadienne

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Corpus-based models of lexical strength have called into question the role of word frequency as an organizing principle of the lexicon, revealing that contextual and semantic diversity measures provide a closer fit to lexical behavior data (Adelman et al., 2006;Jones et al., 2012). Contextual diversity measures modify word frequency by ignoring word repetition in context, while semantic diversity measures consider the semantic consistency of contextual word occurrence. Recent research has shown that a better account of lexical organization data is provided by socially based measures of semantic diversity, which encode the communication patterns of individuals across discourses (Johns, 2021b). While most research on contextual diversity has focused on single words, recent corpus-based and experimental evidence suggests that an integral part of language use involves recurrent and more structurally complex units, such as multiword phrases and idioms. The aim of the present work was to determine if contextual and semantic diversity drive lexical organization at the level of multiword units (here, operationalized as idiomatic expressions), in addition to single words. To this end, we analyzed normative ratings of familiarity for 210 English idioms (Libben & Titone, 2008) using a set of contextual, semantic, and socially based diversity measures that were computed from a 55-billion word corpus of Reddit comments. The results confirm the superiority of diversity measures over frequency for multiword expressions, suggesting that multiword units, such as idiomatic phrases, show similar lexical organization dynamics as single words. Public Significance StatementCorpus-based evidence indicates that the ease with which we access single words in the lexicon depends on their contextual and social diversity, rather than their frequency. However, an integral part of our language environment consists also of conventional multiword units like idioms. We demonstrate that contextual and social diversity shape the lexicon also at the level of multiword units and that idioms thus exhibit the same lexical organizational dynamics as single words.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Determining the importance of frequency and contextual diversity in the lexical organization of multiword expressions.

Senaldi¹,

Titone²,

Johns³

2022

Canadian Journal of Experimental Psychology / Revue canadienne

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“…This follows previous work by Thompson et al (2020) examining the relativity of word meanings across languages. To accomplish this, 500 corpora of prominent users on the internet forum Reddit were constructed, following recent work using Reddit to examine distributional properties of words in a communicative environment to examine lexical organization and lexical semantics (Johns, 2021a(Johns, ,b, 2022. A count-based distributional framework (first described in and further explored by Johns, 2021b), which integrates training procedures from neural embedding models, was used to derive semantic representations for words from the user corpora.…”

Section: Discussionmentioning

confidence: 99%

“…Instead, here individual user corpora will be formed from high-level commenters on the internet forum Reddit. This language source has recently been used to examine communicative and socially-based effects in lexical organization (Johns, 2021a(Johns, , 2022Senaldi, Titone, & Johns, 2022) and lexical semantics (Johns, 2021b) using distributional semantic modeling.…”

Section: Models Of Semantic Memorymentioning

confidence: 99%

Determining the Relativity of Word Meanings through the Construction of Individualized Models of Semantic Memory

Johns¹

2022

Preprint

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Distributional models of lexical semantics are capable of acquiring sophisticated representations of word meanings (Kumar, 2020). The main theoretical advantage of this approach is that the model’s demonstrate the systematic connection between the knowledge that people acquire and the experience that humans have with the natural language environment (Landauer & Dumais, 1997). However, linguistic experience is inherently variable and differs radically across people. Recently, Thompson, Roberts, and Lupyan (2020) used distributional modeling to examine how word meanings vary across languages and it was found that there is considerable variability in the meanings of words across languages for most semantic categories. The goal of this article is to examine how variable words meanings are across individual language users within a single language. This was accomplished by assembling 500 individual user corpora attained from the online forum Reddit (Baumgartner et al., 2020). Each user corpus ranged between 3.8 to 32.3 million words each, and a count-based distributional framework (Johns, Mewhort, & Jones, 2019; Johns, 2021) was used to extract word meanings for each user. These representations were then used to estimate the semantic alignment of word meanings across individual language users. It was found that there are significant levels of relativity in word meanings across individuals, and these differences are partially explained by other psycholinguistic factors, such as concreteness, semantic diversity, and social aspects of language usage. These results point to word meanings being fundamentally relative and fluid, with this relativeness being dependent on the individual nature of linguistic experience.

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Demystifying large language models in second language development research

Cong

2025

Computer Speech & Language

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Accounting for item-level variance in recognition memory: Comparing word frequency and contextual diversity

Cited by 9 publications

References 102 publications

Determining the importance of frequency and contextual diversity in the lexical organization of multiword expressions.

Determining the importance of frequency and contextual diversity in the lexical organization of multiword expressions.

Determining the Relativity of Word Meanings through the Construction of Individualized Models of Semantic Memory

Demystifying large language models in second language development research

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