A deterministic scalable algorithm to detect and measure the basic influence role each node plays within a directed network.

Every node plays a certain role in the network and affects the other nodes in its own different way. Given a large dataset of nodes as input, the algorithm provides:

• A ranking of all nodes by influence score
• The typology of influence, the basic influence role
• The influence measure based on influence role
• The level (the role's subcategory based on influence measure)
• An influence score based on generic indegree and outdegree

The algorithm is implemented in the following programming languages:

• Python
• JavaScript

We have six basic influence roles summarized below.

The levels of BIRs are subcategories based on the influence magnitude of every role. Below we have the description of every level and a graph representation of the branch nodes.

Influence measure is a normalized value to quantify the magnitude of influence for each role.

For reliability aims, we provide two research notebooks, that can be also useful as examples, under the folder /research-notebooks, to test the algorithm behavior across both static and dynamic network structures using synthetic datasets.

If you use this software in your work, please cite it as below:

Miceli, D. (2024). Basic Influence Roles (BIRs) [Computer software]. https://github.com/davidemiceli/basic-influence-roles

Or the BibTeX version:

@software{MiceliBasicInfluenceRoles2024,
  author = {Miceli, Davide},
  license = {MIT},
  month = mar,
  title = {{Basic Influence Roles (BIRs)}},
  url = {https://github.com/davidemiceli/basic-influence-roles},
  year = {2024}
}

Basic Influence Roles is an open source project available under the MIT license.