Movie Reviews - Sentiment Analysis

Python 3.5 classification of tweets (positive or negative) using NLTK-3 and sklearn.

An analysis of the twitter data set included in the nltk corpus.

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What is in this repo

• An implementation of nltk.NaiveBayesClassifier trained against 1000 tweets. Implemented in Train_Classifiers.py.
• Using sklearn
  • Naive Bayes:
    • MultinomialNB:
    • BernoulliNB:
  • Linear Model
    • LogisticRegression:
    • SGDClassifier:
  • SVM
    • SVC:
    • LinearSVC:
    • NuSVC:

Implemented in Scikit_Learn_Classifiers.py

• Implemented a voting system to choose the best out of all the learning methods. Implemented in sentiment_mod.py

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Accuracy achieved

Classifiers	Accuracy achieved
nltk.NaiveBayesClassifier	73.0%
ScikitLearn Implementations
BernoulliNB	72.0%
MultinomialNB	75.0%
LogisticRegression	71.0%
SGDClassifier	69.0%
SVC	48.0%
LinearSVC	74.0%
NuSVC	75.0%

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Requirements

The simplest way(and the suggested way) would be to install the the required packages and the dependencies by using either anaconda or miniconda

After that you can do

$ conda update conda
$ conda install scikit-learn nltk

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Downloading the dataset

The dataset used in this package is bundled along with the nltk package.

Run your python interpreter

>>> import nltk
>>> nltk.download('stopwords')
>>> nltk.download('movie_reviews') 

NOTE: You can check system specific installation instructions from the official nltk website

Check if everything is good till now by running your interpreter again and importing these

>>> import nltk
>>> from nltk.corpus import stopwords, movie_reviews
>>> import sklearn
>>> 

If these imports work for you. Then you are good to go!

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Running it

1. Clone the repo

$ git clone https://github.com/aalind0/Movie_Reviews-Sentiment_Analysis
$ cd Movie_Reviews-Sentiment_Analysis

2. Order of running

3. NLTK_Naive_Bayes.py

4. Scikit_Learn_Classifiers.py

5. Voting_Algos.py

6. Hack away!

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So

"So what, Well this is pretty basic!"

Yes, it is but hey we all do start somewhere right?

Coming Up. I am working on a Twitter Sentiment Analysis project which first trains on a given data-set and then takes in the live twitter feeds, analyses them plus plots them for data visualization.

You can follow me on twitter @singh_aalind to keep tabs on it.

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End

Hacked together by Aalind Singh.