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    "info": {
        "author": "Michael Chary",
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        "description": "Python files for Toxicovigilance on Twitter\r\n\r\nWhat is it?\r\n------------\r\n\r\n A collection of Python files, also listed on PyPI, as part of an ongoing effort to use Twitter for toxicology research. \r\n\r\nHow do I use it?\r\n-----------------\r\n\r\n The easiest thing is to copy all of the files to someplace in your PYTHONPATH, like ~/bin. \r\n\r\n RUN PYTHON MAIN.PY \r\n\r\n This module creates a twitteryQuery.py object for all drugs listed in the formulary. It can save the results in JSON or XLS. \r\n\r\n\r\nWhat other Python Plugins do I need?\r\n_____________________________________\r\n\r\n -Numpy/SciPy\r\n -XLRD XLWT\r\n -python-twitter (use pip install twitter not easy_install twitter)\r\n -matplotlib\r\n -simplejson\r\n -networkx\r\n\r\n\r\nWhat do the files besides main.py do?\r\n______________________________________\r\n\r\n--->twitterQuery.py: main.py creates an instance of twitterQuery for each drug in the \"formulary\" that you are \u2026 querying Twitter for. \r\n\r\n--->parser.py loads the JSON format results from querying twitter and formats them for NLP analysis by:\r\n 1. Writing a reduplicated record of the tweets to an XLS file for human rating. (Change filename, which indicates the location of the JSON dump of the twitter query, as needed.) \r\n 2. Making a stemmed corpus to use for semantic analysis, contextual analysis or as input to a classifier. (Change the savename as needed.)\r\n\r\n--->loadTweets.py is a helper function to calculate the Fleisch-Kincaid grade level of a tweet. \r\n\r\n---> medgraph.py draws a degree-rank plot with the social graph as an inset. \r\nATTRIBUTION: This is a modified version of a file from the matplotlib examples gallery.",
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