2014
DOI: 10.1080/17470218.2013.850521
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Subtlex-UK: A New and Improved Word Frequency Database for British English

Abstract: We present word frequencies based on subtitles of British television programmes. We show that the SUBTLEX-UK word frequencies explain more of the variance in the lexical decision times of the British Lexicon Project than the word frequencies based on the British National Corpus and the SUBTLEX-US frequencies. In addition to the word form frequencies, we also present measures of contextual diversity part-of-speech specific word frequencies, word frequencies in children programmes, and word bigram frequencies, g… Show more

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Cited by 977 publications
(803 citation statements)
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“…In Experiment 1, each participant was shown 100 sentences with a high frequency critical 9 distractor (M = 831.8 words per million; Van Heuven et al, 2014), 100 sentences with a low 10 frequency critical distractor (M = 0.2 words per million, Van Heuven, et al, 2014), and 100 11 sentences with a 4-symbol string as a critical distractor (symbol distractors were created by 12 randomly choosing 1 of 24 unique combinations of @, #, % and &). In Experiment 2, each 13 participant was shown 100 sentences in the symbol condition (which was identical to Experiment 14 1), 100 sentences in the repeated condition that contained a critical distractor that was identical to 15 the target word, and 100 sentences in the control condition that contained a critical distractor that 16 was matched on frequency to the target (M = 44.2 words per million; Van Heuven et al, 2014).…”
mentioning
confidence: 99%
See 1 more Smart Citation
“…In Experiment 1, each participant was shown 100 sentences with a high frequency critical 9 distractor (M = 831.8 words per million; Van Heuven et al, 2014), 100 sentences with a low 10 frequency critical distractor (M = 0.2 words per million, Van Heuven, et al, 2014), and 100 11 sentences with a 4-symbol string as a critical distractor (symbol distractors were created by 12 randomly choosing 1 of 24 unique combinations of @, #, % and &). In Experiment 2, each 13 participant was shown 100 sentences in the symbol condition (which was identical to Experiment 14 1), 100 sentences in the repeated condition that contained a critical distractor that was identical to 15 the target word, and 100 sentences in the control condition that contained a critical distractor that 16 was matched on frequency to the target (M = 44.2 words per million; Van Heuven et al, 2014).…”
mentioning
confidence: 99%
“…In Experiment 2, each 13 participant was shown 100 sentences in the symbol condition (which was identical to Experiment 14 1), 100 sentences in the repeated condition that contained a critical distractor that was identical to 15 the target word, and 100 sentences in the control condition that contained a critical distractor that 16 was matched on frequency to the target (M = 44.2 words per million; Van Heuven et al, 2014). 17…”
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confidence: 99%
“…Basically speaking, Word frequency is highly correlated with context frequency (R= 0.98) Relationship between word frequency and context frequency (both shown on logarithmic scale). Gray points show relationship for all words in the Touchstone Applied Science Associates Corpus ( Figure. 2) [45].…”
Section: Discussionmentioning
confidence: 99%
“…Word frequencies were calculated as Zipf values, based on the SUBTLEX-UK corpus (Van Heuven, Mandera, Keuleers, & Brysbaert, 2014). The high frequency words had significantly higher Zipf values (M = 5.24, SD = 0.30) than the low frequency words (M = 3.36, SD = 0.32) (t(59)=30.48, p < 0.001).…”
Section: Methodsmentioning
confidence: 99%