A generic, machine learning-based revision scoring system for MediaWiki
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Revision Scoring

A generic, machine learning-based revision scoring system designed to be used to automatically differentiate damage from productive contributory behavior on Wikipedia.


Using a scorer_model to score a revision::

  import mwapi
  from revscoring import Model
  from revscoring.extractors.api.extractor import Extractor
  with open("models/enwiki.damaging.linear_svc.model") as f:
       scorer_model = Model.load(f)
  extractor = Extractor(mwapi.Session(host="https://en.wikipedia.org",
                                          user_agent="revscoring demo"))
  feature_values = list(extractor.extract(123456789, scorer_model.features))
  {'prediction': True, 'probability': {False: 0.4694409344514984, True: 0.5305590655485017}} 


The easiest way to install is via the Python package installer (pip).

pip install revscoring

You may find that some of the dependencies fail to compile (namely scipy, numpy and sklearn). In that case, you'll need to install some dependencies in your operating system.

Ubuntu & Debian:

  • Run sudo apt-get install python3-dev g++ gfortran liblapack-dev libopenblas-dev
  • Run apt-get install aspell-ar aspell-bn aspell-is myspell-cs myspell-nl myspell-en-us myspell-en-gb myspell-en-au myspell-et voikko-fi myspell-fr myspell-de-at myspell-de-ch myspell-de-de myspell-he myspell-hr myspell-hu aspell-id myspell-it myspell-nb myspell-fa aspell-pl myspell-pt myspell-es hunspell-sr aspell-sv aspell-ta myspell-ru myspell-uk hunspell-vi aspell-el myspell-lv aspell-ro myspell-ca hunspell-gl




Using Homebrew and pip, installing revscoring and enchant can be accomplished as follows::

  • brew install aspell --with-all-languages
  • brew install enchant
  • pip install --no-binary pyenchant revscoring

Adding languages in aspell (MacOS only)

cd /tmp
wget http://ftp.gnu.org/gnu/aspell/dict/pt/aspell-pt-0.50-2.tar.bz2
bzip2 -dc aspell-pt-0.50-2.tar.bz2 | tar xvf -
cd aspell-pt-0.50-2
sudo make install

The differences between the aspell and myspell dictionaries can cause some of the tests to fail

Finally, in order to make use of language features, you'll need to download some NLTK data. The following command will get the necessary corpora.

python -m nltk.downloader omw sentiwordnet stopwords wordnet

You'll also need to install enchant <https://en.wikipedia.org/wiki/Enchant_(software)>_ compatible dictionaries of the languages you'd like to use. We recommend the following:

  • languages.arabic: aspell-ar
  • languages.bengali: aspell-bn
  • languages.bosnian: hunspell-bs
  • languages.catalan: myspell-ca
  • languages.czech: myspell-cs
  • languages.croatian: myspell-hr
  • languages.dutch: myspell-nl
  • languages.english: myspell-en-us myspell-en-gb myspell-en-au
  • languages.estonian: myspell-et
  • languages.finnish: voikko-fi
  • languages.french: myspell-fr
  • languages.galician: hunspell-gl
  • languages.german: myspell-de-at myspell-de-ch myspell-de-de
  • languages.greek: aspell-el
  • languages.hebrew: myspell-he
  • languages.hungarian: myspell-hu
  • languages.icelandic: aspell-is
  • languages.indonesian: aspell-id
  • languages.italian: myspell-it
  • languages.latvian: myspell-lv
  • languages.norwegian: myspell-nb
  • languages.persian: myspell-fa
  • languages.polish: aspell-pl
  • languages.portuguese: myspell-pt
  • languages.serbian: hunspell-sr
  • languages.spanish: myspell-es
  • languages.swedish: aspell-sv
  • languages.tamil: aspell-ta
  • languages.russian: myspell-ru
  • languages.ukrainian: aspell-uk
  • languages.vietnamese: hunspell-vi