Word Frequencies in Written and Spoken English

Leech, Geoffrey; Rayson, Paul; Wilson, Andrew (All Of Lancaster Universit

doi:10.4324/9781315840161

Cited by 193 publications

(216 citation statements)

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“…For example, for the idiom bear in mind, the first word bear was replaced by another word hold to form a non-formulaic sequence hold in mind. We have made an effort to make sure that the number of syllables of the replacement items was equal to or smaller than that of the formulaic sequence, and the words used as the replacement words were matched in frequency on the basis of BNC frequency list (Leech et al, 2001). There are 30 matched novel phrases in the study; c) 15 ungrammatical sequences were constructed which were used as the distracters in the study.…”

Section: Methodsmentioning

confidence: 99%

The Processing on Different Types of English Formulaic Sequences

Li¹

2015

ELT

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Formulaic sequences are found to be processed faster than their matched novel phrases in previous studies. Given the variety of formulaic types, few studies have compared processing on different types of formulaic sequences. The present study explored the processing among idioms, speech formulae and written formulae. It has been found that in addition to the processing advantage of formulaic sequences as compared to the nonformulaic phrases, frequent written formulaic sequences were processed faster than the infrequent idioms. The results suggested that when processing advantage was concerned, both the holistic storage view and the frequency effect need to be considered.

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Section: Methodsmentioning

confidence: 99%

The Processing on Different Types of English Formulaic Sequences

Li¹

2015

ELT

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“…In essence, the sentiment features provided in the DAL lexica claim only to hold for individual lexical forms, not for all forms of lemmas, while the other three lexica make the assumption that features hold across all forms of a lemma. The use of the WFWSE BNC frequency lists (Leech et al 2001), in fact, solves this potential problem as it provides both lemma and full form counts for all BNC lexical items and so the assumptions of both lexicon types can be upheld, full form counts are used for DAL and lemma counts for the other lexica. Thirdly, a further 24 A. Devitt, K. Ahmad discrepancy between the lexica is their provision of part-of-speech (POS) tags for lexical items.…”

Section: Lexical Features and Frequencies For Corpus Analysismentioning

confidence: 99%

“…This decision was motivated by the size (100 million words), broadness of coverage (10% spoken and 90% written text across a range of topics and registers) and accessibility of the corpus. In fact, the analysis is based on the BNC term frequencies as published in Leech et al (2001) and available on-line at http://www.comp.lancs.ac.uk/ucrel/bncfreq/flists.html. The term frequencies are provided as alphabetical lists of both lemmas and full forms with part-of-speech tags and frequencies reported per million words of the BNC.…”

Section: General Language Corpusmentioning

confidence: 99%

Is there a language of sentiment? An analysis of lexical resources for sentiment analysis

Devitt

Ahmad

2013

Lang Resources & Evaluation

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In recent years, sentiment analysis (SA) has emerged as a rapidly expanding field of application and research in the area of information retrieval. In order to facilitate the task of selecting lexical resources for automated SA systems, this paper sets out a detailed analysis of four widely used sentiment lexica. The analysis provides an overview of the coverage of each lexicon individually, the overlap and consistency of the four resources and a corpus analysis of the distribution of the resources' lexical contents in general and specialised language. This work aims to explore the characteristics of affective language as represented by these lexica and the implications of the findings for developers of sentiment analysis systems.

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“…The term frequency effect claims that subjects respond more rapidly and more accurately to higher-frequency words than to lower-frequency words in tasks of lexical decision (Whaley, 1978;Grainger, 1990), and that speed naming by healthy adults and adults with aphasia is higher for higher-frequency words than for lower-frequency words (Forster & Chambers, 1973;Kay & Ellis, 1987;Grainger, 1990;Kittredge et al, 2008). Objective measurement of this (psycho)linguistic property is based on calculation of word frequency per 1 million words extracted from large corpora (Leech, Rayson & Wilson, 2001). Word frequency in linguistic studies is calculated more often using this objective method than using the subjective method.…”

Section: Subjective Frequency and Imageabilitymentioning

confidence: 99%

Imageability and subjective frequency of the 500 rated nouns in the Croatian Lexical Database

Kraljević¹,

Olujić²

2018

suvlin

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Imageability and subjective frequency of the 500 rated nouns in the Croatian Lexical DatabaseProperties such as word class, length, phonological and morphological complexity, concreteness, frequency, age of acquisition, and imageability have to be controlled in research and clinical practice, since they strongly affect the speed and accuracy of language processing by monolinguals and bilinguals as well as by speakers with language disorders. The purpose of this paper is to present the online Croatian Lexical Database (Cro. Hrvatska leksi~ka baza [HLB], http://polin-hlb.erf.hr/) that contains different (psycho)linguistic word properties, and to use the HLB to provide the first analyses about (1) the relationship between frequency and imageability for the rated 500 nouns, and (2) the influence of raters' age, gender and education on their judgement. The results indicate a significant positive correlation between noun frequency and imageability, but no significant influence of the three non-linguistic rater factors on judgements about (psycho)linguistic property.

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Word Frequencies in Written and Spoken English

Cited by 193 publications

References 0 publications

The Processing on Different Types of English Formulaic Sequences

The Processing on Different Types of English Formulaic Sequences

Is there a language of sentiment? An analysis of lexical resources for sentiment analysis

Imageability and subjective frequency of the 500 rated nouns in the Croatian Lexical Database

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