Metadata-Version: 2.1
Name: influence_model
Version: 0.1.1
Summary: A Python implementation of the influence model, a generative model that describes the interactions between networked Markov chains
Project-URL: Homepage, https://github.com/keelerh/influence-model
Project-URL: Bug Tracker, https://github.com/keelerh/influence-model/issues
Author-email: Keeley Erhardt <keeley@mit.edu>
License-File: LICENSE
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.7
Description-Content-Type: text/markdown

influence-model
========

`influence_model` is a Python implementation of the influence model, a generative model that describes the interactions between networked Markov chains.

**Why influence_model?** It provides an efficient and well-documented implementation of Asavathiratham's influence model, and supports defining new influence models as well as generating observations through applying the model's evolution equations.

Install _influence-model_ by: 

```
pip install influence-model
```

If you find this library helpful to your work, please cite the following paper:

@article{Erhardt_Hidden_Messages_Mapping_2023,
    author = {Erhardt, Keeley and Pentland, Alex},
    doi = {10.0000/00000},
    journal = {Computational and Mathematical Organization Theory},
    month = sep,
    number = {3},
    pages = {1--10},
    title = {{Hidden Messages: Mapping Nations’ Media Campaigns}},
    volume = {29},
    year = {2023}
}
