Network Science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive and semantic networks, and social networks, considering distinct elements or actors represented by nodes (or vertices) and the connections between the elements or actors as links (or edges). The field draws on theories and methods including graph theory from mathematics, statistical mechanics from physics, data mining and information visualization from computer science, inferential modeling from statistics, and social structure from sociology.
The United States National Research Council defines Network Science as “the study of network representations of physical, biological, and social phenomena leading to predictive models of these phenomena.”
—Wikipedia, “Network science”
Today [Network Science] informs all sorts of pursuits, from generating algorithmic recommendations on Facebook to mapping terrorist networks to, yes, forecasting the spread of lethal diseases. But when Rényi got started, he wanted the answer to a simple question: What would a network organized completely at random look like? How would it behave?
—WIRED, “The Vulnerable Can Wait. Vaccinate the Super-Spreaders First: Who gets priority when Covid-19 shots are in short supply? Network theorists have a counterintuitive answer: Start with the social butterflies.“
Why, Vespignani wondered, were computer networks still susceptible to viruses even though millions of individual users had antivirus software? The answer, he discovered, was that if you didn’t inoculate the nodes, malicious code could still zip around the internet with relative ease.
The Vulnerable Can Wait. Vaccinate the Super-Spreaders First Read More