bellert / structural-imbalance-demo Goto Github PK

Social networks map relationships between people or organizations onto graphs, with the people/organizations as nodes and relationships as edges; for example, Facebook friends form a social network with friends represented as nodes with connecting edges. Signed social networks map both friendly and hostile relationships by setting the values of the edges between nodes with either plus ("+") or minus ("-") signs. Such networks are said to be structurally balanced when they can be clearly divided into two, with friendly relations (represented by positive-valued edges) in each faction, and hostile relations (negative-valued edges) between these factions.

The measure of structural imbalance or frustration for a signed social network is the minimum number of edges that violate this rule.

Social theory suggests that increased frustration predicts social instability. In the context of militant organizations, this can result in increased violence.

This demo calculates and shows structural imbalance for social networks of militant organization based on data from the Stanford Militants Mapping Project:

Mapping Militant Organizations, Stanford University, last modified February 28, 2016, http://web.stanford.edu/group/mappingmilitants/cgi-bin/.

Copy (clone) this structural-imbalance-demo repository to your local machine.

In the root directory of your copy of this repository, execute one of the following two commands:

pip install .[cpu]

pip install .[qpu]

Access to a D-Wave system must be configured, as described in the dwave-cloud-client documentation. A default solver is required.

To run the demo, execture one of the following two commands:

python demo.py cpu

python demo.py qpu

The demo fetches data from the Stanford Militants Mapping Project, calculates the networks, and saves PNG-formatted graphic files and CSV-formatted files in the root directory of your copy of the demo repository and in a Results subdirectory.

Note that this CLI command runs the entire demo and can take a few minutes to complete. You can easily modify the code to run just parts of the demo from within a Python interpreter.

See LICENSE file.