- Network Science with Python and NetworkX Quick Start Guide
- Edward L. Platt
- 193字
- 2021-06-24 15:18:49
Network science
The origins of network science trace back to many different fields. For the most part, researchers in these fields developed the tools and methods of network science without much knowledge of how it was being applied in other fields. It may seem astonishing that scientists working independently in very different fields could develop tools and techniques similar enough to now be considered a single field.
How did this happen? The answer lies in one insight: sometimes, it is useful to study the relationships between things without worrying about the specifics of what those things are. Network scientists didn't study networks for their own sake* – they studied networks in order to better understand people, animal species, atoms, and so on. (* Except for mathematicians. We like to think about weird abstract concepts such as networks just for fun.)
When the specifics of the people/species/atoms being studied were abstracted away, seemingly different problems suddenly became very similar. And that's the power of network science; it provides a general language to talk about relationships and connections, allowing discoveries about one thing to be translated into useful information about many other types of things.
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