Text Mining: Sentiment Classifier: Difference between revisions
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* SentiWordNet http://sentiwordnet.isti.cnr.it | * SentiWordNet http://sentiwordnet.isti.cnr.it | ||
==Cara Install== | |||
Perintah shell | |||
python setup.py install | python setup.py install | ||
==Dokumen== | |||
http://readthedocs.org/docs/sentiment_classifier/en/latest/ | |||
Try Online | Try Online | ||
==Penggunaan== | |||
Perintah shell | |||
senti_classifier -c file/with/review.txt | senti_classifier -c file/with/review.txt | ||
Python | ==Penggunaan Python== | ||
Perintah shell | |||
cd sentiment_classifier/src/senti_classifier/ | cd sentiment_classifier/src/senti_classifier/ | ||
python senti_classifier.py -c reviews.txt | python senti_classifier.py -c reviews.txt | ||
Library | ==Penggunaan Library== | ||
from senti_classifier import senti_classifier | from senti_classifier import senti_classifier | ||
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pos_score, neg_score = senti_classifier.polarity_scores(sentences) | pos_score, neg_score = senti_classifier.polarity_scores(sentences) | ||
print pos_score, neg_score | print pos_score, neg_score | ||
Revision as of 02:21, 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
Cara Install
Perintah shell
python setup.py install
Dokumen
http://readthedocs.org/docs/sentiment_classifier/en/latest/ Try Online
Penggunaan
Perintah shell
senti_classifier -c file/with/review.txt
Penggunaan Python
Perintah shell
cd sentiment_classifier/src/senti_classifier/ python senti_classifier.py -c reviews.txt
Penggunaan Library
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
