Various heuristics for maximizing influence in social networks
This project requires Snap (which only works with python 2.7, and is not available via pip), install it here
It also requires networkx-metis (for which the pip install does not work), install it here
Then, install the requirements using pip install -r requirements.txt
The following files will run various heuristics, and output the influence of the best found set. The input parameter k corresponds to the size of the initial set of activated nodes.
python greedy_linear.py [k]
python partition_linear.py [k]
You can also use the independent cascade model by doing:
python greedy_cascade.py [k]
python partition_cascade.py [k]
This project is licensed under the MIT License - see the LICENSE.md file for details
- David Kempe, Jon Kleinberg, and Éva Tardos, "Maximizing the Spread of Influence through a Social Network," 2003
- Aditya Bhaskara