Common English Word

An Common English Word is a Common Word within the English Language.

• AKA: English Common Word.
  • …
• Example(s):
  • “we”.
  • “water”.
  • “woman”.
  • an English Stopword.
  • …
• Counter-Example(s):
  • “antidisestablishmentarianism”, an Uncommon Word in the English Language.
  • “hidden Markov model”, Technical Term.
  • “nous”, a French Common Word.
  • “The Olympic Games”, a Named Entity.
  • a Common German Word.
  • a Common Chinese Word.
• See: English Lexicon, Oxford English Corpus, to be.

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References

• http://www.wordfrequency.info/free.asp

2016

• (Wikipedia, 2016) ⇒ http://wikipedia.org/wiki/Most_common_words_in_English Retrieved:2016-4-11.
  • The list below of most common words in English cannot be definitive. It is based on an analysis of the Oxford English Corpus of over a billion words, and represents one study done by Oxford Online, associated with the Oxford English Dictionary. This source includes writings of all sorts from "literary novels and specialist journals to everyday newspapers and magazines and from Hansard to the language of chatrooms, emails, and weblogs", unlike some sources which use texts from only specific sources.

    The Reading Teacher's Book of Lists claims that the first 25 words make up about one-third of all printed material in English, and that the first 100 make up about one-half of all written material.

    Note that "word" may mean either a word form (essentially, a distinct spelling), or a lexeme (essentially, a "base" word or dictionary-entry). For instance the lexeme "be", listed below, includes occurrences of "are", "is", "were", "was", etc. Note also that these top 100 lemmas listed below account for 50% of all the words in the Oxford English Corpus.

Rank Word 1 the 2 be 3 to 4 of 5 and 6 a 7 in 8 that 9 have 10 I 11 it 12 for 13 not 14 on 15 with 16 he 17 as 18 you 19 do 20 at

Rank Word 21 this 22 but 23 his 24 by 25 from 26 they 27 we 28 say 29 her 30 she 31 or 32 an 33 will 34 my 35 one 36 all 37 would 38 there 39 their 40 what

Rank Word 41 so 42 up 43 out 44 if 45 about 46 who 47 get 48 which 49 go 50 me 51 when 52 make 53 can 54 like 55 time 56 no 57 just 58 him 59 know 60 take

Rank Word 61 people 62 into 63 year 64 your 65 good 66 some 67 could 68 them 69 see 70 other 71 than 72 then 73 now 74 look 75 only 76 come 77 its 78 over 79 think 80 also

Rank Word 81 back 82 after 83 use 84 two 85 how 86 our 87 work 88 first 89 well 90 way 91 even 92 new 93 want 94 because 95 any 96 these 97 give 98 day 99 most 100 us

1991

• (Brown et al., 1991) ⇒ Peter F. Brown, Stephen A. Della Pietra, Vincent J. Della Pietra, and Robert L. Mercer. (1991). “Word-Sense Disambiguation Using Statistical Methods.” In: Proceedings of the 29th annual meeting on Association for Computational Linguistics (ACL 1991) doi:10.3115/981344.981378
  • QUOTE: We used the flip-flop algorithm in a pilot experiment in which we assigned two senses to each of the 500 most common English words and two senses to each of the 200 most common French words. Since the entropy of the translation of a common word can be as high as five bits, there is reason to hope that using more senses will further improve the performance of our system.

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