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Web application for analyzing text sentiment. Messages are input by the user, and classified as Positive or Negative. Supports signup, user authentication, and server-side storage of user data.

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nickwinsley/SentimentAnalyzer

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Description: Webpage for analyzing natural language sentiment. Uses Naive Bayes and the Bag-of-words model (implemented with Python) to classify text sentiment as "Positive" or "Negative".

Example Output:

Usage Instructions for Linux:

Step 1: Install and start Docker if necessary. Open the terminal and enter docker build -t myapp . to build the Docker image. To run the application, enter docker run -d -p 8080:8080 myapp, or alternatively docker run -d -p 8080:8080 -v $(pwd)/data:/app/data myapp to save server-side user data for future logins.

Step 2: Open a new tab in any browser and enter the url http://localhost:8080/.

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Web application for analyzing text sentiment. Messages are input by the user, and classified as Positive or Negative. Supports signup, user authentication, and server-side storage of user data.

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