Outbreak Detection

Detecting outbreak and optimizing objective functions by using different Algorithms:

• Naive Greedy algorithm
• CELF
• Heuristic approaches(based on inlinks, outlinks, followers, ...)

Datasets

Put higgs dataset files in dataset/(or unzip dataset.zip)

higgs-mention_network.edgelist
higgs-reply_network.edgelist
higgs-retweet_network.edgelist
higgs-social_network.edgelist

Usage

python3 main.py --help
usage: main.py [-h] [-test {1,0}] -g {mt,rt} -b BUDGET -obj {DL,DT,PA} {algorithm,heuristic} ...

Find the best placement for outbreak detection

positional arguments:
  {algorithm,heuristic}
                        sub command help
    algorithm           algorithm: choose algorithms and objective functions
    heuristic           heuristic: use heuristic methods to find placement

options:
  -h, --help            show this help message and exit
  -test {1,0}, --test {1,0}
                        Whether to use a smaller dataset for testing
  -g {mt,rt}, --graph {mt,rt}
                        indicate which graph to use, mt(mention) or rt(retweet)
  -b BUDGET, --budget BUDGET
                        total budget
  -obj {DL,DT,PA}, --objective_function {DL,DT,PA}
                        objective functions

Visualization

See visualization.ipynb

References

[1] M. De Domenico, A. Lima, P. Mougel, and M. Musolesi. 2013. The Anatomy of a Scientific Rumor. Scientific Reports 3 (2013), 2980.

[2] J. Leskovec, A. Krause, C. Guestrin, C. Faloutsos, J. VanBriesen, and N. S. Glance. 2007. Cost-effective outbreak detection in networks. In Proceedings of the 13th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 420–429.