Sentiment Analysis Using NLTK

The Modules used for Basic Sentiment Analysis Project are:

• Pandas - Data Munging, Reading / Writing Data Frames
• NLTK - Natural Language Tool Kit- an open source library in Python for Natural Language Processing
• RE - Regular Expression for text processing
• Matplotlib - Plotting and Visualization
• String - Dealing with String data

Basic Steps in NLP Project:

• Data Collection
• Data Preparation
• Model Selection
• Model Building
• Model Training
• Evaluation
• Fine Tuning and Testing

Data Selection

Using the Pre-Loaded data from NLTK

from nltk.corpus import twitter_samples

all_positive_tweets = twitter_samples.strings('positive_tweets.json')

all_negative_tweets = twitter_samples.strings('negative_tweets.json')

Data Visualization

fig = plt.figure(figsize=(5, 5))

labels = 'Positives', 'Negative'

sizes = [len(all_positive_tweets), len(all_negative_tweets)] 

plt.pie(sizes, labels=labels, autopct='%1.1f%%', shadow=True, startangle=90)

plt.axis('equal')  

plt.show()