# Network Theory- 14 Network Dynamics

Almost all real networks are dynamic in nature and how they have evolved and change over time is a defining feature to their topology and properties. As network theory is a very new subject much of it is still focused on trying to explore the basics of static graphs, as the study of their dynamics results in the additional of a whole new sets of parameters to our models and takes us in to a new level of complexity, much of which remains unexplored, and is the subject of active research.

For full courses, transcriptions & downloads please see: http://www.complexityacademy.io

Transcription excerpt: So lets start by talking about growing a random network to see what it looks like, when we say growing a network we might mean adding more nodes to it, but also, more interestingly adding links to it, that increases the overall connectivity. In our random model links were just placed between nodes at random with some given probability, growing the network here just meant increasing this probability so as to have more links develop over time. One interesting thing we find when we do this is that there are thresholds and phase transitions during the network's development, by thresholds we simply mean that, by gradually increasing our link probability parameter, some property to the network suddenly appearing when we pass a critical value.

So for example our first threshold is when the average degree goes above 1 over the total number of nodes in the network, as at this threshold…

- Kind: Short
- Year: 2015
- Runtime: 6 min
- By: Complexity Academy
- Genres: Science
- Archive: [Wikimedia Commons](https://commons.wikimedia.org/wiki/File:Network_Theory-_14_Network_Dynamics.webm)
- Licence or status: [CC BY 3.0](https://creativecommons.org/licenses/by/3.0) (as the archive states it)
- Credit: Complexity Academy
- Who can watch: Tweens profiles and older (the archive gives no rating; placed by Invisible Network from its collection and subjects)

[Watch now](https://invisiblenetwork.ai/watch/archive/commons/57997228?play=1)