“The Corpus of Contemporary American English (COCA) is the largest freely-available corpus of English, and the only large and balanced corpus of American English. The corpus was created by Mark Davies of Brigham Young University, and it is used by tens of thousands of users every month (linguists, teachers, translators, and other researchers). COCA is also related to other large corpora that we have created. “The corpus contains more than 450 million words of text and is equally divided among spoken, fiction, popular magazines, newspapers, and academic texts. It includes 20 million words each year from 1990-2012 and the corpus is also updated regularly (the most recent texts are from Summer 2012). Because of its design, it is perhaps the only corpus of English that is suitable for looking at current, ongoing changes in the language (see the 2011 article in Literary and Linguistic Computing)The interface allows you to search for exact words or phrases, wildcards, lemmas, part of speech, or any combinations of these. You can search for surrounding words (collocates) within a ten-word window (e.g. all nouns somewhere near faint, all adjectives near woman, or all verbs near feelings), which often gives you good insight into the meaning and use of a word. The corpus also allows you to easily limit searches by frequency and compare the frequency of words, phrases, and grammatical constructions, in at least two main ways:
- By genre: comparisons between spoken, fiction, popular magazines, newspapers, and academic, or even between sub-genres (or domains), such as movie scripts, sports magazines, newspaper editorial, or scientific journals
- Over time: compare different years from 1990 to the present time
You can also easily carry out semantically-based queries of the corpus. For example, you can contrast and compare the collocates of two related words (little/small, democrats/republicans, men/women), to determine the difference in meaning or use between these words. You can find the frequency and distribution of synonyms for nearly 60,000 words and also compare their frequency in different genres, and also use these word lists as part of other queries. Finally, you can easily create your own lists of semantically-related words, and then use them directly as part of the query.”
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