This project conducts a network analysis of characters in the Game of Thrones series using Python.
The data used in this analysis consists of interactions between characters in the Game of Thrones series. The dataset includes information about the characters involved, the type of interaction, and the context of the interaction.
To conduct the network analysis, the following Python libraries are used:
- NetworkX: A library for creating and analyzing complex networks.
- nxviz: A package for visualizing NetworkX graphs.
- Community: A module for community detection in networks.
- NumPy: A library for numerical computing in Python.
- Pandas: A powerful data analysis and manipulation library.
- Matplotlib: A comprehensive library for creating static, animated, and interactive visualizations in Python.
- Seaborn: A statistical data visualization library based on Matplotlib.
To install the required libraries, run the following command:
!pip install nxviz
To conduct the network analysis and visualize the results, run the provided Python script or Jupyter Notebook. Make sure to have the required libraries installed as mentioned in the Libraries Used section.
The analysis covers various aspects of the Game of Thrones network, including:
- Book-wise comparison of character interactions.
- Centrality measures such as degree, eigenvector, betweenness, and closeness centrality.
- Evolution of character interactions throughout the series.
- PageRank analysis to identify influential characters.
- Independent cascade model for predicting information spread in the network.
- Dispersion analysis to explore the connections between specific characters.
The analysis provides insights into the structure of the Game of Thrones network and the importance of different characters throughout the series.
Contributions to this project are welcome. If you have ideas for improving the analysis, adding new features, or fixing issues, feel free to fork the repository and submit a pull request.