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Introduction

WatchComplexity is a Machine Learning framework to understand and analyze complex networks and more in general complex data. It is a collection of clustering techniques inspired by social science and communication theories.

Implementation

Is is written in pure javascript, but one of the next steps of development could be to organize it as microservices to be used via REST APIs by other languages.

Motivation

Our main goal is to do experimental research with practical applications.

Index of contents

• Introduction
• Installation
• Algorithms
  • Ranked Influence Typology
  • Network Similarity
• Testing

License

WatchComplexity is available under the MIT license.