"Albert-Laszlo Barabasi, the nation's foremost expert in the new science of networks, takes us on an intellectual adventure to prove that social networks, corporations, and living organisms are more similar than previously thought. A full understanding of network science will someday enhance our ability to design blue-chip businesses, stop the outbreak of deadly diseases, and influence the exchange of ideas and information. Engaging and authoritative, Linked provides an exciting glimpse into the next century of science and an urgent new perspective on our interconnected world. Book jacket."--
Outlines a theory of how to predict behavior, drawing on seven years of research while demonstrating the mathematical properties of seemingly random events, from the spread of epidemics to the history of wars
We've long suspected that we live in a small world, where everything is connected to everything else. Indeed, networks are pervasive--from the human brain to the Internet to the economy to our group of friends. These linkages, it turns out, aren't random. All networks, to the great surprise of scientists, have an underlying order and follow simple laws. Understanding the structure and behavior of these networks will help us do some amazing things, from designing the optimal organization of a firm to stopping a disease outbreak before it spreads catastrophically. In Linked, Barab(c)Łsi, a physicist whose work has revolutionized the study of networks, traces the development of this rapidly unfolding science and introduces us to the scientists carrying out this pioneering work. These "new cartographers" are mapping networks in a wide range of scientific disciplines, proving that social networks, corporations, and cells are more similar than they are different, and providing important new insights into the interconnected world around us. This knowledge, says Barab(c)Łsi, can shed light on the robustness of the Internet, the spread of fads and viruses, even the future of democracy
"Networks are everywhere, from the Internet, to social networks, and the genetic networks that determine our biological existence. Illustrated throughout in full colour, this pioneering textbook, spanning a wide range of topics from physics to computer science, engineering, economics and the social sciences, introduces network science to an interdisciplinary audience. From the origins of the six degrees of separation to explaining why networks are robust to random failures, the author explores how viruses like Ebola and H1N1 spread, and why it is that our friends have more friends than we do. Using numerous real-world examples, this innovatively designed text includes clear delineation between undergraduate and graduate level material"--Page [4] of cover
Abstract References, the mechanism scientists rely on to signal previous knowledge, lately have turned into widely used and misused measures of scientific impact. Yet, when a discovery becomes common knowledge, citations suffer from obliteration by incorporation. This leads to the concept of hidden citation, representing a clear textual credit to a discovery without a reference to the publication embodying it. Here, we rely on unsupervised interpretable machine learning applied to the full text of each paper to systematically identify hidden citations. We find that for influential discoveries hidden citations outnumber citation counts, emerging regardless of publishing venue and discipline. We show that the prevalence of hidden citations is not driven by citation counts, but rather by the degree of the discourse on the topic within the text of the manuscripts, indicating that the more discussed is a discovery, the less visible it is to standard bibliometric analysis. Hidden citations indicate that bibliometric measures offer a limited perspective on quantifying the true impact of a discovery, raising the need to extract knowledge from the full text of the scientific corpus.
From the Internet to networks of friendship, disease transmission, and even terrorism, the concept--and the reality--of networks has come to pervade modern society. But what exactly is a network? What different types of networks are there? Why are they interesting, and what can they tell us? In recent years, scientists from a range of fields--including mathematics, physics, computer science, sociology, and biology--have been pursuing these questions and building a new "science of networks." This book brings together for the first time a set of seminal articles representing research from acros
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Understanding of modern government is limited by a lack of comprehensive, reliable, comparable data on what governments do and how they are organized to execute their diverse responsibilities. We demonstrate that such data can be collected from the extensive footprint that governments leave on the Internet, opening a range of unresolved puzzles and questions about modern government to closer empirical inquiry. The online footprint of the 50 US state governments reflects their close embeddedness with state economies and suggests that other factors widely hypothesized to influence government play more limited roles, including location and income. It also casts doubt on the degree to which state government functional structures systematically reflect voters' recent ideological preferences.
