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Word frequency is known to have various effects (Brysbaert et al. 2011; Rudell 1993). Memorization is positively affected by higher word frequency, likely because the learner is subject to more exposures (Laufer 1997). Lexical access is positively influenced by high word frequency, a phenomenon called word frequency effect (Segui et al.).
The General Service List (GSL) is a list of roughly 2,000 words published by Michael West in 1953. [1] The words were selected to represent the most frequent words of English and were taken from a corpus of written English. The target audience was English language learners and ESL teachers. To maximize the utility of the list, some frequent ...
This list contains Germanic elements of the English language which have a close corresponding Latinate form. The correspondence is semantic—in most cases these words are not cognates, but in some cases they are doublets, i.e., ultimately derived from the same root, generally Proto-Indo-European, as in cow and beef, both ultimately from PIE *gʷōus.
In English this means one word inherited from a Germanic source, with, e.g., a Latinate cognate term borrowed from Latin or a Romance language. In English this is most common with words which can be traced back to Indo-European languages, which in many cases share the same proto-Indo-European root, such as Romance beef and Germanic cow.
These are 1100 of the most common words in American English in order of usage. This can be a particularly useful list when starting to learn a new language and will help prioritise creating sentences using the words in other languages to ensure that you develop your core quickly.
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Some lists of common words distinguish between word forms, while others rank all forms of a word as a single lexeme (the form of the word as it would appear in a dictionary). For example, the lexeme be (as in to be) comprises all its conjugations (is, was, am, are, were, etc.), and contractions of those conjugations. [5]
This ground-breaking new dictionary, which first appeared in 1969, was the first dictionary to be compiled using corpus linguistics for word frequency and other information. The initial Brown Corpus had only the words themselves, plus a location identifier for each. Over the following several years part-of-speech tags were applied.