Sentiment Analysis Chatbot -- Made By Jayesh Chak (thewabisabiway.learnjc@gmail.com)
//Overview
Welcome to the Sentiment Analysis Chatbot Program! This program is designed to analyze the sentiment of input text using a pre-trained machine learning model. It can provide you with sentiment labels of "positive," "neutral," or "negative" based on the content of your input.
//How to Use
To use this program, follow these simple steps:
-
Download the program: Download the program file (main.py) from the provided source along with data files (.csv and .sav)
-
Run the program: Double-click the main.py file to start the program.
-
Chat with the Chatbot:
- You can interact with the chatbot by typing text inputs in double quotation marks.
- Type your input and press Enter to receive a sentiment analysis.
-
End the Conversation:
- Type "exit" to end the conversation and close the program.
- The chatbot will thank you, and the conversation will be saved.
//Terms and Conditions
By using this program, you agree to the following terms and conditions:
-
Data Collection: This program may collect and store the input text you provide for analysis purposes. Your data will be used solely for sentiment analysis and will not be shared with third parties.
-
Accuracy: The sentiment analysis provided by this program is generated by a machine learning model and may not always be 100% accurate. It should be used as a general indication of sentiment and not for critical decisions.
-
Data Usage: Any data provided to this program will be stored locally for the purpose of maintaining conversation history and improving the program's performance. The data will not be used for any other purposes.
-
Acknowlegments: This program uses open-source libraries and resources. We acknowledge and programreciate the contributions of the developers and organizations behind these libraries.
//Acknowledgments
We would like to express our gratitude to the following individuals and organizations for their contributions to this program:
- The scikit-learn development team for the scikit-learn library.
- The developers of the TextBlob library for natural language processing.
- The NLTK team for providing resources and tools for natural language processing.
- The open-source community for making various resources and tools available for use.
- The Teachnook Community for mentorship, guidance, support and resources.
Your contributions have been invaluable in the development of this program.