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Analyse sentiments of popular music lyrics over time
Jupyter Notebook Python
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README.md
charts.py
lyrics-analysis-playground.ipynb
lyrics.py
requirements.txt
speech-analysis.py

README.md

lyrics-analysis

WORK IN PROGRESS

Fooling around with APIs to analyse sentiments of popular music lyrics over time

Components

  • charts.py gets the top-10 charts for every month for the last 20 years from billboard.com
  • lyrics.py uses these charts and adds lyrics to every song. Uses the Mixmatcher API (needs an API key)
  • speech-analysis.py uses the data from lyrics.py and runs every song through the Google Natural Language API to do a sentiment analysis. It awards a score from -1.0 (negative) to +1.0 (positive)
  • Every script outputs the data to a JSON-File in the same directory. Subsequent parts use these files if they exist

APIs

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