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        "author": "Valerij Fredriksen and Brage Ekroll Jahren and Mats Byrkjeland",
        "author_email": "matsbyr@gmail.com",
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            "Programming Language :: Python :: 3",
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            "Programming Language :: Python :: 3.4",
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        "description": "Lexicon Classifier\n==================\n\nSource code: https://github.com/draperunner/fjlc\n\nThis package is a Python port of the Lexicon Creator and Classifier of\nValerij Fredriksen and Brage Ekroll Jahren (2016). It is compatible with\nPython version >= 3.\n\nThe original Java code is available here:\nhttps://github.com/freva/Masteroppgave\n\nIf using this package in your publications, please cite > Valerij\nFredriksen and Brage Ekroll Jahren. Twitter Sentiment Analysis:\nExploring Automatic Creation of Sentiment Lexica. Master's thesis, 2016.\n\nInstallation\n------------\n\n.. code:: bash\n\n    pip install fjlc\n\nLexicon Classifier\n------------------\n\nThe ``LexiconClassifier`` uses the best performing lexicon of Fredriksen\nand Jahren. You can specify your own lexicon, see Options below.\n\nUsage\n~~~~~\n\n.. code:: python\n\n    from fjlc import LexiconClassifier\n    lc = LexiconClassifier()\n\nYou can classify a single tweet or a list of tweets:\n\n::\n\n    >>> lc.classify(\"I am happy!\")\n    'POSITIVE'\n    >>> lc.classify([\"I am happy!\", \"I hate rain\"])\n    ['POSITIVE', 'NEGATIVE']\n\nYou can get the sentiment value of a single tweet or multiple tweets\n\n::\n\n    >>> lc.classify(\"I am happy!\")\n    5.599244615570646\n    >>> lc.classify([\"I am happy!\", \"I hate rain\"])\n    [5.599244615570646, -2.767224666516315]\n\nOptions\n~~~~~~~\n\nThe ``LexiconClassifier`` takes three options: \\* ``lexicon``: Path to\nsentiment lexicon file \\* ``options``: Path to options file \\*\n``dictionary``: Path to canonical dictionary\n\nLexicon Creator\n---------------\n\nUsage\n~~~~~\n\n.. code:: python\n\n    from fjlc import LexiconCreator\n    lc = LexiconCreator()\n\nIncomplete, untested.",
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