Difference between revisions of "Text Mining: Sentiment Classifier"
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Onnowpurbo (talk | contribs) (Created page with "Sentiment Classifier using Word Sense Disambiguation using wordnet and word occurance statistics from movie review corpus nltk. Classifies into positive and negative categorie...") |
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| − | Sentiment Classifier | + | Sentiment Classifier menggunakan Word Sense Disambiguation menggunakan WordNet dan statistik terjadinya kata dari corpus movie review NLTK. Mengklasifikasikan ke dalam kategori positif dan negatif. |
| − | + | ==Persyaratan== | |
| − | + | * Python 2.6. | |
| − | + | * NLTK http://www.nltk.org 2.0 | |
| − | + | * NumPy http://numpy.scipy.org | |
| − | + | * SentiWordNet http://sentiwordnet.isti.cnr.it | |
| − | |||
| − | |||
How to Install | How to Install | ||
Revision as of 09:19, 3 February 2017
Sentiment Classifier menggunakan Word Sense Disambiguation menggunakan WordNet dan statistik terjadinya kata dari corpus movie review NLTK. Mengklasifikasikan ke dalam kategori positif dan negatif.
Persyaratan
- Python 2.6.
- NLTK http://www.nltk.org 2.0
- NumPy http://numpy.scipy.org
- SentiWordNet http://sentiwordnet.isti.cnr.it
How to Install
Shell command
python setup.py install
Documentation
http://readthedocs.org/docs/sentiment_classifier/en/latest/ Try Online
Script Usage
Shell Commands:
senti_classifier -c file/with/review.txt
Python Usage
Shell Commands
cd sentiment_classifier/src/senti_classifier/ python senti_classifier.py -c reviews.txt
Library Usage
from senti_classifier import senti_classifier sentences = ['The movie was the worst movie', 'It was the worst acting by the actors'] pos_score, neg_score = senti_classifier.polarity_scores(sentences) print pos_score, neg_score