Moving beyond Kučera and Francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English

By Marc Brysbaert, Boris New. Behavior Research Methods, 2009

2,492 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cognitive Neuroscience, Developmental and Educational Psychology

View Paper: https://www.semanticscholar.org/paper/12b3581395cf7d07aeb3774cbfa3a42837ee87bf

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Citations in the corpus

Concreteness ratings for 40 thousand generally known English word lemmas (2014, methodology): “The SUBTLEX-US frequency count (on a total of 51 million; Brysbaert & New, 2009) Figure 1: Distribution of the concreteness ratings (N = 39,954): 1 = very abstract (languagebased ), 5 = very concrete (experience-based).”
Effects of primary and secondary morphological family size in monolingual and bilingual word processing (2014, methodology): “These family size values were collin ar with the values of the logarithmically transformed values of SBTLWF (English Subtitle Frequency per million; Brysbaert & New, 2009).”
Age-of-acquisition ratings for 30,000 English words (2012, methodology): “Finally, the quality of the first phoneme of a word, or its place or manner of articulation, is the most influential variable in word naming (Balota et al., 2004; Yap & Balota, 2009) and auditory lexical decision (Yap & Brysbaert, 2009).”
The Word Frequency Effect in Word Processing: An Updated Review (2018, background): “This suggests that the difference in frequency effect is not related to differences in intelligence (second-language speakers, on average, are not less intelligent than native speakers) but to differences in language exposure, which can be measured with a vocabulary test (Brysbaert, Lagrou, & Steven”
Taste and smell words form an affectively loaded and emotionally flexible part of the English lexicon (2016, neutral): “, 2011) with measures of valence (Warriner, Kuperman & Brysbaert, 2013; Mohammad, 2012). This is done for adjectives, nouns and verbs. The adjective data comes from Lynott and Connell (2009), who asked fifty-five native speakers of English to judge a set of 423 object properties on each of the five ”
Frequency in lexical processing (2016, background): “…language, corpora consisting of film subtitles, which are straightforward to extract from existing resources on the web, have recently been compiled (Brysbaert, Keuleers, & New, 2011; Brysbaert & New, 2009; Keuleers, Stevens, Mandera, & Brysbaert, 2015; New, Brysbaert, Veronis, & Pallier, 2007).”
Linguistic Features Identify Alzheimer’s Disease in Narrative Speech (2015, neutral): “Specifically, we use the SUBTL frequency norms [53] and the combined Bristol and Gilhooly-Logie norms [54, 55] for familiarity, imageability, and age-ofacquisition.”