metadata

license: mit
task_categories:
  - token-classification
language:
  - en
size_categories:
  - 100K<n<1M
datasets:
  - movie_network_analysis
tags:
  - network analysis
  - community detection
  - centrality measures
  - python
  - data science

Movie Network Analysis

Dataset Summary

This dataset contains information about top-rated films and their shared actors, used to conduct network analysis and understand the factors contributing to their success. The analysis employs techniques like network construction, community detection, and centrality measures.

Motivation

The motivation behind this project is to explore connections between successful films through shared actors, aiming to provide insights that could benefit filmmakers and industry stakeholders in optimizing film production decisions.

Data

Code Files

data_collection.py: Python script to collect data from TMDB API, cleanse it, and prepare it for analysis.
network_construction.py: Script to construct the film network based on shared actors and compute edge weights.
analysis.py: Contains functions for performing network analysis using algorithms like PageRank, Louvain community detection, and degree centrality.
utils.py: Utility functions used across the scripts for data preprocessing and calculation.

Data Files

top_films_data.csv: CSV file containing details of the top-rated films used in the analysis, including budget, revenue, genres, actors, etc.
film_network.graphml: GraphML file representing the film network with nodes as films and weighted edges based on shared actors.

Usage

Setup Instructions

To run the scripts and replicate the analysis:

Prerequisites:

Python 3.x installed.
Required Python packages installed (listed in requirements.txt).

Installation:

pip install -r requirements.txt

Running the Scripts

Adjust configurations (API keys, file paths) in the scripts if necessary.
Execute each script in the following order:

python data_collection.py
python network_construction.py
python analysis.py

Output

Check generated output files (film_network.graphml, etc.) for results of the analysis.

Additional Notes

Ensure API keys and paths to data files are correctly configured in the scripts.
For detailed explanations of algorithms and methodologies used, refer to the comments within each script.
For any questions or issues, contact the contributors listed above.

Contributors

Jay Sharma
Saiz Prasla
Harsimran Saini
Zuhair Siddiqi

License

This project is licensed under the MIT License.