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Observe that average word length appears to be a general property of English, since it has a recurrent value of variable counts space characters.) By contrast average sentence length and lexical diversity appear to be characteristics of particular authors.

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NLTK's small collection of web text includes content from a Firefox discussion forum, conversations overheard in New York, the movie script of There is also a corpus of instant messaging chat sessions, originally collected by the Naval Postgraduate School for research on automatic detection of Internet predators.

The corpus contains over 10,000 posts, anonymized by replacing usernames with generic names of the form "User NNN", and manually edited to remove any other identifying information.

The corpus is organized into 15 files, where each file contains several hundred posts collected on a given date, for an age-specific chatroom (teens, 20s, 30s, 40s, plus a generic adults chatroom).

The filename contains the date, chatroom, and number of posts; e.g., The Brown Corpus was the first million-word electronic corpus of English, created in 1961 at Brown University.

This chapter continues to present programming concepts by example, in the context of a linguistic processing task.

We will wait until later before exploring each Python construct systematically.

Don't worry if you see an example that contains something unfamiliar; simply try it out and see what it does, and — if you're game — modify it by substituting some part of the code with a different text or word.

This way you will associate a task with a programming idiom, and learn the hows and whys later.

As just mentioned, a text corpus is a large body of text.

Many corpora are designed to contain a careful balance of material in one or more genres.

We examined some small text collections in 1., such as the speeches known as the US Presidential Inaugural Addresses.

This particular corpus actually contains dozens of individual texts — one per address — but for convenience we glued them end-to-end and treated them as a single text. also used various pre-defined texts that we accessed by typing This program displays three statistics for each text: average word length, average sentence length, and the number of times each vocabulary item appears in the text on average (our lexical diversity score).

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