Metadata-Version: 1.1
Name: labMTsimple
Version: 2.8.7
Summary: Basic usage script for dictionary-based sentiment analysis. Intended use with labMT data
Home-page: https://github.com/andyreagan/labMT-simple
Author: Andy Reagan
Author-email: andy@andyreagan.com
License: UNKNOWN
Download-URL: https://github.com/andyreagan/labMT-simple/tarball/2.8.y
Description: labMT-simple
        ============
        
        TL;DR a simple labMT usage script
        
        This script uses the language assessment by Mechanical Turk (labMT) word
        list to score the happiness of a corpus. The labMT word list was created
        by combining the 5000 words most frequently appearing in four sources:
        Twitter, the New York Times, Google Books, and music lyrics, and then
        scoring the words for sentiment on Amazon's Mechanical Turk. The list is
        described in detail in the publication Dodds' et al. 2011, PLOS ONE,
        "Temporal Patterns of Happiness and Information in a Global-Scale Social
        Network: Hedonometrics and Twitter."
        
        Given two corpora, the script "storylab.py" creates a word-shift graph
        illustrating the words most responsible for the difference in happiness
        between the two corpora. The corpora should be large (e.g. at least
        10,000 words) in order for the difference to be meaningful, as this is a
        bag-of-words approach. As an example, a random collection of English
        tweets from both Saturday January 18 2014 and Tuesday January 21 2014
        are included in the "example" directory. They can be compared by moving
        to the test directory, using the command
        
        .. code:: python
        
            python example.py example-shift.html
        
        and opening the file ``example-shift.html`` in a web browser. For an
        explanation of the resulting plot, please visit
        
        http://www.hedonometer.org/shifts.html
        
        Installation
        ------------
        
        Cloning the github directly is recommended, i.e.
        
        .. code:: bash
        
            git clone https://github.com/andyreagan/labMT-simple.git
        
        and then installing locally using
        
        .. code:: bash
        
            sudo python setup.py install
        
        Tests can be run by navigating to the test directory, and running
        
        .. code:: bash
        
            python test.py
        
        which will compare the two days in test/data and print test.html which
        shifts them, allowing for a changable lens.
        
        This repository can also be installed using pip
        
        .. code:: bash
        
            pip install labMTsimple
        
        in which case you can download the tests from github and run them, if
        desired.
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
