https://github.com/beyondmayowo/sentiment-analysis

Sentiment analysis using IBM Watson NLU API
https://github.com/beyondmayowo/sentiment-analysis

flask-application sentiment-analysis watson-nlu-api webapp

Last synced: about 1 year ago
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Sentiment analysis using IBM Watson NLU API

• Host: GitHub
• URL: https://github.com/beyondmayowo/sentiment-analysis
• Owner: beyondmayOwO
• License: apache-2.0
• Created: 2025-01-12T12:09:29.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-01-19T09:43:27.000Z (over 1 year ago)
• Last Synced: 2025-03-23T14:34:43.220Z (over 1 year ago)
• Topics: flask-application, sentiment-analysis, watson-nlu-api, webapp
• Language: Python
• Homepage:
• Size: 2.21 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# sentiment-analysis

Sentiment analysis using IBM Watson NLU API. It can detect the sentiment of the text and the score. Web application deployed on the Flask server.

## Demo

![](demo.gif)

- User can input the sentence and it will detect three sentiment of the text: positive, negative, and neutral

- It will also put the score of the text

- If the input is nonesense, it will displays 'Invalid text'

- If there is no input, it will displays 'Empty input'

## What I Learned

- Created an AI based sentiment analysis application using Watson NLU API.

- Formatted the output received from the Watson NLU API to extract relevant information from it.

- Packaged the application and made it importable to any python code for usage.

- Ran unit tests on the application and checked the validity of its outputs for different inputs.

- Deployed the application using Flask framework.

- Incorporated error handling capability in the application, such that a response code of 500 receives an appropriate response from the application.

- Ran static code analysis on the code files to confirm their adherence to the PEP8 guidelines.