出版社: Plume
副标题: How Everything is Connected to Everything Else and What It Means for Business, Science, and Everyday Life
出版年: 2003
页数: 294
定价: US$ 15.00
装帧: Paperback
ISBN: 9780452284395
内容简介 · · · · · ·
A cocktail party. A terrorist cell. Ancient bacteria. An international conglomerate.
All are networks, and all are a part of a surprising scientific revolution. AlbertLászló Barabási, 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 sim...
A cocktail party. A terrorist cell. Ancient bacteria. An international conglomerate.
All are networks, and all are a part of a surprising scientific revolution. AlbertLászló Barabási, 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. Grasping a full understanding of network science will someday allow us to design bluechip businesses, stop the outbreak of deadly diseases, and influence the exchange of ideas and information. Just as James Gleick brought the discovery of chaos theory to the general public, Linked tells the story of the true science of the future.
作者简介 · · · · · ·
艾伯特拉斯洛·巴拉巴西是圣母院大学教授，主持对于复杂网络的研究。他在多个领域的开创性贡献也屡屡见诸媒体，广受赞誉。他出生于特兰西瓦尼亚，现居住在印第安纳州的南本德（south Bend）。
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书评 · · · · · · (共50条)
我来评论这本书读书笔记 · · · · · ·
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hedgehog (所有的最好都是从最坏开始的)
As long as we thought of networks as random, we modeled them as static graphs. The scalefree model reflects our awakening to the reality that networks are dynamic systems that change constantly through the addition of new nodes and links. The fitness model allows us to describe networks as competitive systems in which nodes fight fiercely for links. Now BoseEinstein condensation explains how som...20130106 11:15
As long as we thought of networks as random, we modeled them as static graphs. The scalefree model reflects our awakening to the reality that networks are dynamic systems that change constantly through the addition of new nodes and links. The fitness model allows us to describe networks as competitive systems in which nodes fight fiercely for links. Now BoseEinstein condensation explains how some winner get the chance to take it all. Do the advances obtained by acknowledeing fitness toss out the scalefree model? By no means. In networks that display fitgetrichh behavior, competition leads to a scalefree topology. Most networks we have studies so far  the Web, the Internet, the cell, Holloywood, and many other real networks  belong to this category. The winner shares the spotlight with a continuous hierarchy of hubs. Yet BoseEinstein condensation offers the theoretical possibility that in some systems the winner can grab all the links. When that happens, the scalefree topology vanishes. So far among real systems, only the operations system market, with Microsoft as its dominating hub, appears to fit the bill. Are there other systems out there displaying a similar behavior? Very likely. It will take some time, however, to recognize them all.
回应 20130106 11:15 
Erdos and Renyi and its clusterfriendly extension by Watts and Strogatz both insisted that the number of nodes with k links should decrease exponentially a much faster decay than that predicted by a power law. Network of pornstars and Hollywood proved that the size does not always matter. The truly center position in networks is reserved for those nodes that are simultaneously part of many la...
20110316 09:34
Erdos and Renyi and its clusterfriendly extension by Watts and Strogatz both insisted that the number of nodes with k links should decrease exponentially a much faster decay than that predicted by a power law.Network of pornstars and Hollywood proved that the size does not always matter. The truly center position in networks is reserved for those nodes that are simultaneously part of many large networks Peaked distribution vs. power law Road map vs. airline mapScale (characteristic note) in random networks vs. hierarchy structure of power lower (real network)scale free80/20 rule and the fact that the networks behind the web, hollywood, scientists and the cell and many other complex systems all obey a power law allowed us toe paraphrase Pareto and claim for the first time that perhaps there were laws behind complex networks.In physics: how does order emerge from disorder?Hubs the consequences of power laws a hint of selforganization and order.Despite the diversity most real networks share an essential feature: growth. It ended up dethroning the first fundamental assumption of the random universe: its static character. Also we abandon another assumption inherent in random networks: democratic character. We find that real networks are governed by two laws: growth and preferential attachment (rich get richer phenomenon).Static versus growing; random versus scalefree, structure versus evolution In terms of topology all networks fall into one of only two possible categories:Scalefree topology: a fitgetrich behavior. We have a hierarchy of nodes whose degree distribution follows a power lawWinner takes all: not scalefree. Destroys the hierarchy of hubs characterizing the scalefree topology.Vulnerability due to interconnectivity A significant fraction of nodes can be randomly removed from any scalefree network without its breaking apart. A property not shared by random networksThe web of life determines whether a cell …”there are no good or bad genes, but only networks that exist at various levels” P181The full weblike molecular architecture of a cell is encoded in the cellular network, a sum of all cellular components, connected by sll physiologically relevant interactions. P183(SYSTEM AND SUB system)回应 20110316 09:34

Erdos and Renyi and its clusterfriendly extension by Watts and Strogatz both insisted that the number of nodes with k links should decrease exponentially a much faster decay than that predicted by a power law. Network of pornstars and Hollywood proved that the size does not always matter. The truly center position in networks is reserved for those nodes that are simultaneously part of many la...
20110316 09:34
Erdos and Renyi and its clusterfriendly extension by Watts and Strogatz both insisted that the number of nodes with k links should decrease exponentially a much faster decay than that predicted by a power law.Network of pornstars and Hollywood proved that the size does not always matter. The truly center position in networks is reserved for those nodes that are simultaneously part of many large networks Peaked distribution vs. power law Road map vs. airline mapScale (characteristic note) in random networks vs. hierarchy structure of power lower (real network)scale free80/20 rule and the fact that the networks behind the web, hollywood, scientists and the cell and many other complex systems all obey a power law allowed us toe paraphrase Pareto and claim for the first time that perhaps there were laws behind complex networks.In physics: how does order emerge from disorder?Hubs the consequences of power laws a hint of selforganization and order.Despite the diversity most real networks share an essential feature: growth. It ended up dethroning the first fundamental assumption of the random universe: its static character. Also we abandon another assumption inherent in random networks: democratic character. We find that real networks are governed by two laws: growth and preferential attachment (rich get richer phenomenon).Static versus growing; random versus scalefree, structure versus evolution In terms of topology all networks fall into one of only two possible categories:Scalefree topology: a fitgetrich behavior. We have a hierarchy of nodes whose degree distribution follows a power lawWinner takes all: not scalefree. Destroys the hierarchy of hubs characterizing the scalefree topology.Vulnerability due to interconnectivity A significant fraction of nodes can be randomly removed from any scalefree network without its breaking apart. A property not shared by random networksThe web of life determines whether a cell …”there are no good or bad genes, but only networks that exist at various levels” P181The full weblike molecular architecture of a cell is encoded in the cellular network, a sum of all cellular components, connected by sll physiologically relevant interactions. P183(SYSTEM AND SUB system)回应 20110316 09:34 
hedgehog (所有的最好都是从最坏开始的)
As long as we thought of networks as random, we modeled them as static graphs. The scalefree model reflects our awakening to the reality that networks are dynamic systems that change constantly through the addition of new nodes and links. The fitness model allows us to describe networks as competitive systems in which nodes fight fiercely for links. Now BoseEinstein condensation explains how som...20130106 11:15
As long as we thought of networks as random, we modeled them as static graphs. The scalefree model reflects our awakening to the reality that networks are dynamic systems that change constantly through the addition of new nodes and links. The fitness model allows us to describe networks as competitive systems in which nodes fight fiercely for links. Now BoseEinstein condensation explains how some winner get the chance to take it all. Do the advances obtained by acknowledeing fitness toss out the scalefree model? By no means. In networks that display fitgetrichh behavior, competition leads to a scalefree topology. Most networks we have studies so far  the Web, the Internet, the cell, Holloywood, and many other real networks  belong to this category. The winner shares the spotlight with a continuous hierarchy of hubs. Yet BoseEinstein condensation offers the theoretical possibility that in some systems the winner can grab all the links. When that happens, the scalefree topology vanishes. So far among real systems, only the operations system market, with Microsoft as its dominating hub, appears to fit the bill. Are there other systems out there displaying a similar behavior? Very likely. It will take some time, however, to recognize them all.
回应 20130106 11:15

hedgehog (所有的最好都是从最坏开始的)
As long as we thought of networks as random, we modeled them as static graphs. The scalefree model reflects our awakening to the reality that networks are dynamic systems that change constantly through the addition of new nodes and links. The fitness model allows us to describe networks as competitive systems in which nodes fight fiercely for links. Now BoseEinstein condensation explains how som...20130106 11:15
As long as we thought of networks as random, we modeled them as static graphs. The scalefree model reflects our awakening to the reality that networks are dynamic systems that change constantly through the addition of new nodes and links. The fitness model allows us to describe networks as competitive systems in which nodes fight fiercely for links. Now BoseEinstein condensation explains how some winner get the chance to take it all. Do the advances obtained by acknowledeing fitness toss out the scalefree model? By no means. In networks that display fitgetrichh behavior, competition leads to a scalefree topology. Most networks we have studies so far  the Web, the Internet, the cell, Holloywood, and many other real networks  belong to this category. The winner shares the spotlight with a continuous hierarchy of hubs. Yet BoseEinstein condensation offers the theoretical possibility that in some systems the winner can grab all the links. When that happens, the scalefree topology vanishes. So far among real systems, only the operations system market, with Microsoft as its dominating hub, appears to fit the bill. Are there other systems out there displaying a similar behavior? Very likely. It will take some time, however, to recognize them all.
回应 20130106 11:15 
Erdos and Renyi and its clusterfriendly extension by Watts and Strogatz both insisted that the number of nodes with k links should decrease exponentially a much faster decay than that predicted by a power law. Network of pornstars and Hollywood proved that the size does not always matter. The truly center position in networks is reserved for those nodes that are simultaneously part of many la...
20110316 09:34
Erdos and Renyi and its clusterfriendly extension by Watts and Strogatz both insisted that the number of nodes with k links should decrease exponentially a much faster decay than that predicted by a power law.Network of pornstars and Hollywood proved that the size does not always matter. The truly center position in networks is reserved for those nodes that are simultaneously part of many large networks Peaked distribution vs. power law Road map vs. airline mapScale (characteristic note) in random networks vs. hierarchy structure of power lower (real network)scale free80/20 rule and the fact that the networks behind the web, hollywood, scientists and the cell and many other complex systems all obey a power law allowed us toe paraphrase Pareto and claim for the first time that perhaps there were laws behind complex networks.In physics: how does order emerge from disorder?Hubs the consequences of power laws a hint of selforganization and order.Despite the diversity most real networks share an essential feature: growth. It ended up dethroning the first fundamental assumption of the random universe: its static character. Also we abandon another assumption inherent in random networks: democratic character. We find that real networks are governed by two laws: growth and preferential attachment (rich get richer phenomenon).Static versus growing; random versus scalefree, structure versus evolution In terms of topology all networks fall into one of only two possible categories:Scalefree topology: a fitgetrich behavior. We have a hierarchy of nodes whose degree distribution follows a power lawWinner takes all: not scalefree. Destroys the hierarchy of hubs characterizing the scalefree topology.Vulnerability due to interconnectivity A significant fraction of nodes can be randomly removed from any scalefree network without its breaking apart. A property not shared by random networksThe web of life determines whether a cell …”there are no good or bad genes, but only networks that exist at various levels” P181The full weblike molecular architecture of a cell is encoded in the cellular network, a sum of all cellular components, connected by sll physiologically relevant interactions. P183(SYSTEM AND SUB system)回应 20110316 09:34
在豆瓣App讨论这本书 · · · · · ·
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其他版本有售
这本书的其他版本 · · · · · · ( 全部4 )
 湖南科技出版社版 20070401 / 628人读过 / 有售
 浙江人民出版社版 201381 / 250人读过 / 有售
 Basic Books版 200205 / 12人读过
以下豆列推荐 · · · · · · ( 全部 )
 复杂网络和社会网络分析 (marego)
 社区研究 (小白)
 i Internet (浪子回头)
 interaction design (bark)
 bEINg A GeEkId (王小飞在豆瓣)
谁读这本书?
二手市场
订阅关于Linked的评论:
feed: rss 2.0
0 有用 peter 20070610
简单而全面地描述了“网络”的核心概念，是网络经济的概念基础
0 有用 tzungtzu 20130722
大牛的书，重读英文版了
0 有用 青铜 20091207
不错的科普
0 有用 煮茶叶蛋 20111104
当年居然以为读了这书就算是学习complex network了。。。想来真是年少无知。作者是提出scale free network的开山学者，文笔也是不错，擅长讲故事，所以书读来还蛮有趣，是个不错的入门读物。不过感觉这书里多少有些做广告和忽悠的成分，作者把复杂网络理论渲染得仿佛宇宙头号真理一般，但是其实后来想想多少也有些夸张了。
0 有用 阿邪兔 20120721
这家伙是鼻祖又怎样？一点儿也没觉得这本书多好，尤其是和Connected相比。
0 有用 JIDISI 20141119
成为我的导师吧，先生！
0 有用 Avner Journey 20140502
inspiring
0 有用 suya 20150618
透过网络理解社会。Power Law，小世界比比皆是。了解互联网形成的启蒙读物。一个道理不同事例贯穿全篇。
0 有用 tzungtzu 20130722
大牛的书，重读英文版了
0 有用 Gandalf 20140428
One of those books that changes how you look at the world.