"Every network has its own fitness distribution, which tells us how similar or different the nodes in the network are. In networks where most of the nodes have comparable fitness, the distribution follows a narrowly peaked bell curve. In other networks, the range of fitnesses is very wide such that a few nodes are much more fit than most others. […] the mathematical tools developed decades earlier to describe quantum gases enabled us to see that, independent of the nature of links and nodes, a network's behavior and topology are determined by the shape of its fitness distribution. But even though each system, from the Web to Holywood, has a unique fitness distribution, Bianconi's calculation indicated that in terms of topology all networks fall into one of only two possible categories. In most networks the competition does not have an easily noticeable impact on the network's topology. In some networks, however, the winner takes all the links, a clear signature of Bose-Einstein condensation." (Albert-László Barabási, "Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life", 2002)
"In a random network the peak of the distribution implies that the vast majority of nodes have the same number of links and that nodes deviating from the average are extremely rare. Therefore, a random network has a characteristic scale in its node connectivity, embodied by the average node and fixed by the peak of the degree distribution. In contrast, the absence of a peak in a power-law degree distribution implies that in a real network there is no such thing as a characteristic node. We see a continuous hierarchy of nodes, spanning from rare hubs to the numerous tiny nodes. The largest hub is closely fol - lowed by two or three somewhat smaller hubs, followed by dozens that are even smaller, and so on, eventually arriving at the numerous small nodes." (Albert-László Barabási, "Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life", 2002)
"[…] most earlier attempts to construct a theory of complexity have overlooked the deep link between it and networks. In most systems, complexity starts where networks turn nontrivial. No matter how puzzled we are by the behavior of an electron or an atom, we rarely call it complex, as quantum mechanics offers us the tools to describe them with remarkable accuracy. The demystification of crystals-highly regular networks of atoms and molecules-is one of the major success stories of twentieth-century physics, resulting in the development of the transistor and the discovery of superconductivity. Yet, we continue to struggle with systems for which the interaction map between the components is less ordered and rigid, hoping to give self-organization a chance." (Albert-László Barabási, "Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life", 2002)
"Most systems displaying a high degree of tolerance against failures are a common feature: Their functionality is guaranteed by a highly interconnected complex network. A cell's robustness is hidden in its intricate regulatory and metabolic network; society's resilience is rooted in the interwoven social web; the economy's stability is maintained by a delicate network of financial and regulator organizations; an ecosystem's survivability is encoded in a carefully crafted web of species interactions. It seems that nature strives to achieve robustness through interconnectivity. Such universal choice of a network architecture is perhaps more than mere coincidences." (Albert-László Barabási, "Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life", 2002)
"Nature normally hates power laws. In ordinary systems all quantities follow bell curves, and correlations decay rapidly, obeying exponential laws. But all that changes if the system is forced to undergo a phase transition. Then power laws emerge-nature's unmistakable sign that chaos is departing in favor of order. The theory of phase transitions told us loud and clear that the road from disorder to order is maintained by the powerful forces of self-organization and is paved by power laws. It told us that power laws are not just another way of characterizing a system's behavior. They are the patent signatures of self-organization in complex systems." (Albert-László Barabási, "Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life", 2002)
"Networks are not en route from a random to an ordered state. Neither are they at the edge of randomness and chaos. Rather, the scale-free topology is evidence of organizing principles acting at each stage of the network formation process." (Albert-László Barabási, "Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life", 2002)
"[…] networks are the prerequisite for describing any complex system, indicating that complexity theory must inevitably stand on the shoulders of network theory. It is tempting to step in the footsteps of some of my predecessors and predict whether and when we will tame complexity. If nothing else, such a prediction could serve as a benchmark to be disproven. Looking back at the speed with which we disentangled the networks around us after the discovery of scale-free networks, one thing is sure: Once we stumble across the right vision of complexity, it will take little to bring it to fruition. When that will happen is one of the mysteries that keeps many of us going." (Albert-László Barabási, "Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life", 2002)
"[…] real networks not only are connected but are well beyond the threshold of one. Random network theory tells us that as the average number of links per node increases beyond the critical one, the number of nodes left out of the giant cluster decreases exponentially. That is, the more links we add, the harder it is to find a node that remains isolated. Nature does not take risks by staying close to the threshold. It well surpasses it." (Albert-László Barabási, "Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life", 2002)
"Regular graphs are unique in that each node has exactly the same number of links. […] Such regularity is clearly absent from random graphs. The premise of the random network model is deeply egalitarian: We place the links completely randomly; thus all nodes have the same chance of getting one […] If the network is large, despite the links' completely random placement, almost all nodes will have approximately the same number of links." (Albert-László Barabási, "Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life", 2002)
"The difference between human dynamics and data mining boils down to this: Data mining predicts our behaviors based on records of our patterns of activity; we don't even have to understand the origins of the patterns exploited by the algorithm. Students of human dynamics, on the other hand, seek to develop models and theories to explain why, when, and where we do the things we do with some regularity." (Albert-László Barabási, "Bursts: The Hidden Pattern Behind Everything We Do", 2010)
"A key discovery of network science is that the architecture of networks emerging in various domains of science, nature, and technology are similar to each other, a consequence of being governed by the same organizing principles. Consequently we can use a common set of mathematical tools to explore these systems." (Albert-László Barabási, "Network Science", 2016)
"Although cascading failures may appear random and unpredictable, they follow reproducible laws that can be quantified and even predicted using the tools of network science. First, to avoid damaging cascades, we must understand the structure of the network on which the cascade propagates. Second, we must be able to model the dynamical processes taking place on these networks, like the flow of electricity. Finally, we need to uncover how the interplay between the network structure and dynamics affects the robustness of the whole system." (Albert-László Barabási, "Network Science", 2016)
"And that’s what good networkers do. No matter the field, discipline, or industry, if we want to succeed, we must master the networks. Because as the First Law of Success reminds us, the harder it is to measure performance, the less performance matters." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)
"[…] because performance is so bounded, it allows us to predict, with impressive accuracy, what our own ultimate limit." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)
"Credit for teamwork isn’t based on performance. Credit is based on perception." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)
"Diversity creates the best mix for success, but for that mix to be potent, it needs a leader. Indeed, the more successful a team is in the programming universe, the more lopsided the contributions are to the work. A single leader emerges who calls the shots and does most of the programming. To be sure, his fellow contributors also play a vital role, offering key expertise and filling in the holes. But it’s the leader who makes the project whole, correcting individual errors, rejecting pieces he considers subpar, and ensuring that the final product matches his vision and standards." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)
"Networks brim with opportunity, partially because they’re held together by powerful hubs, people who are, well… really good at networking. These connectors are eager to utilize their relationships to support people and causes they find value in. They’re especially good at seeing opportunities in the social fabric that other people miss. Connect with them." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)
"[…] once a project is successful, it will grow indefinitely, in proportion to previous success." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)
"Performance drives success, but when performance can’t be measured, networks drive success." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)
"Performance is bounded, no matter your profession, which makes distinguishing among top performers inevitably difficult." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)
"Remember, performance needs to be empowered by opportunity. We need to reframe the all-too-frequent assumption that aiming for the top means scraping our way up from the bottom. " (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)
"Scientific analysis can illuminate seemingly deeply irrational puzzles, turning our assumptions on their heads. In other words, science can help us make sense of the randomness of the human world—unveiling the mechanisms at work when we’re passed over for a job, the underlying pattern that explains why some artists thrive while others fail, the lingering hunch that success is about more than just talent or how well we perform." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)
"Since success is a collective phenomenon, measured by how our community reacts to a performance, it’s impossible to understand the phenomenon of success without also observing the network it takes place within. But networks are singularly important in areas like art, where performance and quality are hard to measure." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)
"Successful teams require balance and diversity. But they also need a leader." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)
"While team success requires diversity and balance, a single individual will receive credit for the group’s achievements." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)
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