Text Mood Analyzer

Text Mood Analyzer is a Python application that analyzes the sentiment and similarity of textual data using various natural language processing libraries such as NLTK, TextBlob, SpaCy, Gensim, and CoreNLP via the stanza library.

Features

• Sentiment analysis using NLTK, TextBlob, SpaCy, and CoreNLP.
• Text similarity comparison using Word2Vec from Gensim.
• Easy-to-use command-line interface.
• Supports multiple natural language processing techniques for accurate sentiment analysis and text similarity assessment.

Requirements

• Python 3.x
• NLTK
• TextBlob
• SpaCy
• Gensim
• stanza

Installation

Clone this repository:

git clone https://github.com/your-username/text-mood-analyzer.git

Install the required dependencies:

pip install -r requirements.txt

Download the necessary NLTK corpora:

python -m nltk.downloader punkt

python -m nltk.downloader vader_lexicon

Download the English language model for CoreNLP using stanza:

python -m stanza.download en

Usage Run the application: python main.py Follow the prompts to enter the text for sentiment analysis and text similarity comparison.

License This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments This project was inspired by the need for a simple yet effective sentiment analysis tool. Special thanks to the developers of NLTK, TextBlob, SpaCy, Gensim, and CoreNLP for their invaluable contributions to the field of natural language processing.