kevincobain2000 / Sentiment_classifier
Projects that are alternatives of or similar to Sentiment classifier
Citations
This library is sited here.
http://www.aclweb.org/anthology/W14-2708
iPhone App for Twitter Sentiments is Out
https://itunes.apple.com/us/app/emotion-calculator-for-twitter/id591404584?ls=1&mt=8
App no longer available. Sorry Due to lack of funds to run a seperate server App has been taken out of the app store. Use it free to build your own app tho
Sentiment Classification using WSD, Maximum Entropy & Naive Bayes Classifiers
- pip install sentiment_classifier
-
Home <http://www.jaist.ac.jp/~s1010205/>
_ -
pypi package <http://pythonpackages.com/package/sentiment_classifier>
_ -
Github <https://github.com/kevincobain2000/sentiment_classifier>
_
Overview
Sentiment Classifier using Word Sense Disambiguation using wordnet
and word occurance
statistics from movie review corpus nltk
. For twitter sentiment analysis bigrams are used as
features on Naive Bayes and Maximum Entropy Classifier from the twitter data. Classifies into positive and negative labels.
Next is use senses instead of tokens from the respective data.
.. raw:: html
sentiment_classifier-0.5.tar.gz
<iframe src="http://www.jaist.ac.jp/~s1010205/cgi-bin/pypi-git-stats/stats.cgi?pypi=sentiment_classifier&gituser=kevincobain2000&repo=sentiment_classifier" allowtransparency="true" frameborder="0" scrolling="0" width="180px" height="45px"></iframe>
Download Stats Provided by
pypi-github-stats <http://www.jaist.ac.jp/~s1010205/pypi-git-stats/>
_
Sentiment Classifiers and Data
The above online demo uses movie review corpus from nltk, twitter and Amazon,on which Naive Bayes classifier is trained. Classifier using WSD SentiWordNet is based on heuristics and uses WordNet and SentiWordNet. Test results on sentiment analysis on twitter and amazon customer reviews data & features used for NaiveBayes will be Github <https://github.com/kevincobain2000/sentiment_classifier>
_.
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+ or Python 3.4+.
- 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
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
.. code-block:: python
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
.. code-block:: python
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
.. include:: run_time.rst .. include:: disqus_jnlp.html.rst