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README.md
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README.md
@ -2,6 +2,7 @@ Tools for working with word frequencies from various corpora.
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Author: Robyn Speer
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## Installation
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wordfreq requires Python 3 and depends on a few other Python modules
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@ -21,11 +22,25 @@ install them on Ubuntu:
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sudo apt-get install mecab-ipadic-utf8 libmecab-dev
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pip3 install mecab-python3
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## Unicode data
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The tokenizers that split non-Japanese phrases utilize regexes built using the
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`unicodedata` module from Python 3.4, which supports Unicode version 6.3.0. To
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update these regexes, run `scripts/gen_regex.py`.
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## Tokenization
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wordfreq uses the Python package `regex`, which is a more advanced
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implementation of regular expressions than the standard library, to
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separate text into tokens that can be counted consistently. `regex`
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produces tokens that follow the recommendations in [Unicode
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Annex #29, Text Segmentation][uax29].
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There are language-specific exceptions:
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- In Arabic, it additionally normalizes ligatures and removes combining marks.
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- In Japanese, instead of using the regex library, it uses the external library
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`mecab-python3`. This is an optional dependency of wordfreq, and compiling
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it requires the `libmecab-dev` system package to be installed.
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- It does not yet attempt to tokenize Chinese ideograms.
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[uax29]: http://unicode.org/reports/tr29/
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## License
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@ -56,5 +71,5 @@ sources:
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Some additional data was collected by a custom application that watches the
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streaming Twitter API, in accordance with Twitter's Developer Agreement &
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Policy. This software only gives statistics about words that are very commonly
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used on Twitter; it does not display or republish any Twitter content.
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Policy. This software gives statistics about words that are commonly used on
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Twitter; it does not display or republish any Twitter content.
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