A Python-based application that leverages a sentiment analysis tool to analyze the sentiment of social media text data. It provides insights into whether text content is positive, negative, neutral, or extremely positive/negative. The project includes three main components: a sentiment analysis module, a social media text analyzer, and a user-friendly application to run the analysis.
The project employs the sentiment analysis tool to categorize text data into the following sentiment labels:
- Extremely Positive
- Very Positive
- Positive
- Extremely Negative
- Very Negative
- Negative
- Neutral
The SocialMediaAnalyzer class can analyze a list of social media texts and provide sentiment results for each text, making it suitable for batch processing.
The SocialMediaApp class serves as an easy-to-use interface for running sentiment analysis on social media texts. It allows users to load data from a file, view sentiment results, visualize the sentiment distribution, and save results to an output file.
To use the Social Media Sentiment Analyzer, follow these steps:
- Install the required Python dependencies (NLTK and Matplotlib) using
pip:
pip install nltk matplotlib