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UML classifiers for SemEval 2015
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README.md

TwitterHawk

Classifiers for SemEval 2015 Tasks.

SemEval 2015 http://alt.qcri.org/semeval2015/task10/

Installation

Install of these python modules via pip:

    - nltk
    - pyenchant
    - numpy
    - BeautifulSoup
    - twitter
    - scikit-learn

    - scipy
    - nltk
    - nose


Must create a BISCUIT_DIR environment variable.

    - Will hopefully be eliminated soon.


Install the ark_tweet_nlp project for tokenization of tweets

    - git clone https://github.com/ianozsvald/ark-tweet-nlp-python.git
    - Set the config file to refer to the directory that you just cloned

Task B

$ cd ./TaskB/code
$ python train.py      # takes about 70s for me
$ python predict.py    # takes about 30s for me

W. Boag, P. Potash, A. Rumshisky. TwitterHawk: A Feature Bucket Approach to Sentiment Analysis, In Proceedings of the 9th international workshop on Semantic Evaluation Exercises (SemEval-2015), June 2015, Denver, Colorado, USA. http://www.cs.uml.edu/~wboag/research/publications/wboag-twitterhawk.pdf

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