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Social network analysis done on a dataset of top 1000 IMDB movies

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IMDB Top1000 movie data analysis

The goal of this project was to take the dataset of top 1000 IMDB movies from 2006 up to 2016 and apply several social network analysis techniques on it.

The three main graphs we are interested in are:

  • Actor co-ocurence graph
  • Genre relation graph
  • Movie relation graph

The analysis was done in Jupyter Notebook, as well as Gephi for visualizing the generated graphs.
All of the used data is available in this repository, as well as on Kaggle.

Configuration

Using Python 3.6.7 do:

pip install -r requirements
jupyter notebook

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Social network analysis done on a dataset of top 1000 IMDB movies

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