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https://github.com/kevincobain2000/sentiment_classifier
Sentiment Classification using Word Sense Disambiguation
https://github.com/kevincobain2000/sentiment_classifier
machine-learning sentiment-analysis word-sense-disambiguation wsd
Last synced: about 1 month ago
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Sentiment Classification using Word Sense Disambiguation
- Host: GitHub
- URL: https://github.com/kevincobain2000/sentiment_classifier
- Owner: kevincobain2000
- License: other
- Created: 2012-02-02T07:40:39.000Z (almost 13 years ago)
- Default Branch: master
- Last Pushed: 2022-04-05T01:04:07.000Z (almost 3 years ago)
- Last Synced: 2024-11-08T01:53:01.507Z (2 months ago)
- Topics: machine-learning, sentiment-analysis, word-sense-disambiguation, wsd
- Language: OpenEdge ABL
- Homepage:
- Size: 24.1 MB
- Stars: 172
- Watchers: 11
- Forks: 33
- Open Issues: 0
-
Metadata Files:
- Readme: README
- License: LICENSE.txt
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README
Sentiment Classification using WSD
==================================
- ``pip install sentiment_classifier``
- `Home `_
- `Download `_
- `Github `_
- `Try Online `_
Overview
--------
Sentiment Classifier using Word Sense Disambiguation using ``wordnet`` and word occurance
statistics from movie review corpus ``nltk``. Classifies into positive and negative categories.
Online Demo
-----------
- `Try Online `_
Requirements
------------
In ``Version 0.5`` all the following requirements are installed automatically. In case of troubles install those manually.
- You must have Python 2.6.
- NLTK http://www.nltk.org 2.0 installed.
- NumPy http://numpy.scipy.org
- SentiWordNet http://sentiwordnet.isti.cnr.it
How to Install
--------------
Shell command ::
python setup.py install
Documentation
-------------
- http://pythonhosted.org/sentiment_classifier/
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
... 0.0 1.75
::
from senti_classifier.senti_classifier import synsets_scores
print synsets_scores['peaceful.a.01']['pos']
... 0.25
History
=======
- ``0.7`` Python 3.0 suport Thanks to @MrLokans
- ``0.6`` Bug Fixed upon nltk upgrade
- ``0.5`` No additional data required trained data is loaded automatically. Much faster/Optimized than previous versions.
- ``0.4`` Added Bag of Words as a Feature as occurance statistics
- ``0.3`` Sentiment Classifier First app, Using WSD module