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Network Science 2 Networks and Network Research in the 21st Century If there is one word to describe society in the early 21st century, it surely must be “connected.” We have grown up taking for granted the vast interlinked networks that bring electricity, water, gas, and cable TV to our homes and that allow us to be in personal contact with others almost anywhere in the world by telephone, e-mail, and other communications means. The Internet, especially the World Wide Web (www), is thoroughly ingrained in our everyday lives. The defense of our nation is heavily dependent on electronic networks for communication, command and control, collaborative decision making, intelligence gathering, and other critical functions. While less obviously “networks,” many other richly connected systems play crucial roles in our lives. When diseases are transmitted by person-to-person contact, their spread patterns and ultimate effect are highly dependent on connections that can be described as a network. When cells divide and transform under the influence of minute amounts of biochemical elements in the body, they trigger a network of influences and dependent reactions. Human organizations are networks, often captured graphically with organization charts. In our daily lives we encounter health-care provider networks, purchase goods from companies that acquired them from supply networks, and pay for them using networks of banks and credit card companies. Our brains are immense networks of highly interconnected nerve cells, responsible for our ability to see and hear, make decisions, remember and learn, and act. In order to get a sense of the scope and character of these networks, the committee classified them into biological (e.g., metabolic pathways), physical (e.g., the power grid and telephone system), and social (e.g., governments and churches). This taxonomy is developed in Table 2-1, which identifies some important physical, social, and biological networks and gives an indication of their global impact. This table illustrates clearly the utter pervasiveness of networks in every aspect not only of human existence but also of the existence of all living entities on planet Earth. Connectivity is an essential ingredient of life as we know it. Not only are networks pervasive, they are astonishingly diverse. Moreover, they can be characterized by figures of merit that indicate how large, how complicated, how robust, and how important they are. This aspect of networks is illustrated in Table 2-2, which shows the characteristics of a diverse sampling of networks. The figures of merit for the columns are defined in the footnotes. This table is worthy of close examination because it reveals the wide diversity of the scales, structures, states of maturity, technological intensity, benefits, and consequences of failure of some of the networks that we encounter daily. It also illustrates how complex some of the networks are, leading one to wonder if their designers and operators can control their behaviors. Inspection of Tables 2-1 and 2-2 leads to the committee’s first finding: Finding 2-1. Networks enable the necessities and conveniences of modern life. The tables illustrate how vital networks are to modern life. We see from them that networks underlie nearly every aspect of the infrastructure that supports daily life. Electricity, water, transportation, telephone service, Internet connection, health care, banking, shopping, education, and government all are brought to us by physical or social networks. Our bodies and minds are also manifestations of networks. The natural world in which we live is a vast array of ecological networks. Networks are ubiquitous in daily life. They also are central to the global economic infrastructure. The failure of any of these networks impacts society. Finding 2-2. Engineered networks are a major driver of the increasingly global economy and can be of benefit to both the United States and its competitors. It can be seen from these tables that modern communications and transportation networks are the drivers of the global economy. They provide the fundamental connectivity on which global banking, product design, tourism, supply chain
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Network Science TABLE 2-1 Representative Networks Biological Networksa Physical Networks Social Networks Type of Network Global Impact Type of Network Global Impact Type of Network Global Impact Disease transmitting networks (HIV, influenza, TB, malaria, cholera) Spread of disease, epidemics Distribution grids (electric power, water supply, business supply chains) Efficient distribution of goods or commodities Affiliation/ acquaintance networks (terrorist, community, business, religious, clubs) Efficient collaboration and activity coordination Ecological networks (food webs, river basins, rain forest) Survival of selected species; global weather and topography Telecommunications infrastructure (cellular, PSTN, cable TV, Internet) Instantaneous worldwide information distribution Broadcast networks (radio, TV networks like NBC, CBS, CNN) Dissemination of identical information to large groups Metabolic networks Sustenance of life for a given generation of living entities DOD global information grid (sensors, communications, and weapons) Network-centric warfare and network-enabled operations Information exchange networks (U.S. mail, local and long-distance telephone service) Cheap, convenient long distance pair-wise communications Community networks (insect societies, animal herds, bird flocks, schools of fish) Survival of selected species Transportation networks (airports, highways, railways, shipping) Rapid movement of goods from supplier to market; modern travel Group forming networks (eBay, corporate intranets) Easy, convenient formation of groups of like-minded people who have never met Gene expression networks Transmission and evolution of life between generations Electronic financial transaction networks (banking, credit cards, ATMs) Electronic cashless transactions Supply chains and business networks Coordination of multiple players to achieve common goals, global cost reduction Social services networks (Social Security, family services, Medicare, Medicaid) Efficient delivery of government services to large, distributed constituencies NOTE: PSTN, public switched telephone network; DOD, Department of Defense. aIncludes biochemical and other networks that are natural rather than manmade. management, and customer relationship management depend. From overseas manufacturer to Wal-Mart, products are ordered electronically, produced on demand, shipped around the globe by shipping networks, and delivered to local stores by rail and truck networks. Heralded by some pundits as the century of biology and nanotechnology, the 21st century is in fact an era of networks and is called by others “The Age of Information and Telecommunications” (Perez, 2002). Finding 2-3. Social and biological networks bear important similarities to engineered networks. One might infer from Table 2-1 that biological and social networks are similar to engineered networks. Indeed, much recent literature has been devoted to documenting just how this is the case (Barabási, 2002; Bower and Bolouri, 2001; Dorogovtsev and Mendes, 2003; Newman, 2003; Watts, 2003). The important point for this study is that many methods and models are applicable to networks of all kinds: biological, physical, and social. (These commonalities are explored in Chapter 5 and Appendix C.) Finding 2-4. Advances in computer-based technologies and telecommunications are enabling social networks that facilitate group affiliations, including terrorist networks. An important property of networks is that they may be built on top of each other. For example, a social network may be formed based on an information network built on a communications network that utilizes a physical network of transmission equipment. This property enables experimentation in the social network realm using commercial com-
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Network Science TABLE 2-2 Maturity, Structure, Characteristics, and Impacts of Some Networks Sample Network Relative Maturitya (High, Medium, Low) Network Structureb Technology Intensityc (High, Medium, Low) Network Scoped Representative Societal Impacts/Benefits Societal Impact of Catastrophic Failuree (High, Low) Catastrophic Failure Description Number of Nodes Topology Complexity Scaling U.S. electric power distribution grid High High Low N Medium National Electric lighting, appliances, and electronics High Continent-spanning blackout Air transportation network High Medium Medium N**2 High Regional/ national/ global Rapid global transport of people and cargo Low Major weather-related delays Integrated circuits (chip level) Medium Medium Medium N**2 High Local Ubiquitous computing and other electronic devices Low Device failure or recall Cellular network and public switched telephone network High High Low N High National/ global Instantaneous mobile worldwide communications High Surge-caused outage during a crisis Sexual networks (e.g., those leading to or spreading HIV or sexual diseases) N/A Low Low N N/A Mostly local, but with modern transportation can be regional, national, or global Large segments of population afflicted with AIDS in underdeveloped world High Onset of global pandemic Internet data-link layer (router) topology High Medium High N**2 High Global Enabler of Web and electronic commerce Low Major denial-of-service attacks Applications layer Internet topology Medium Medium Medium 2**N High Global Support for group-forming networks Low Computer viruses, spyware, and identification theft Bank of America financial and banking network Medium Medium Low N**2 High National/ global Cashless retailing and electronic currency exchanges High Global disruption of electronic financial transactions Wal-Mart-like business supply chain Low Low Medium 2**N Medium National/ global Just-in-time supply and inventory control Low Stock items not in stores Small (50,000 or less) town governments High Low Medium 2**N Medium Local Roads, water, sewage, zoning, police Low (as individual governments) Loss of local order, e.g., looting aThe network’s position on a scale starting from first generation (at emergence, a low state) and ending with a high state of maturity, by which time the network has gone through multiple subsequent iterations. bNetwork structure is characterized by number of nodes, topology complexity, and scaling. The number of nodes ranges between low (<1,000), medium (1,000 to 10,000,000), and high (>10,000,000). Topology complexity describes the diversity of interconnections from varied and complex to simple and uniform. Scaling means economic or social value of that network as a function of N (the number of nodes). A linear value of N means that service is aimed at individual users. N**2 is the value that results from person-to-person transactions, and 2**N, the value that results from the establishment of group affiliations (Rheingold, 2002, p. 58). cNetwork topology that is enabled by or highly dependent on modern computer-to-computer communications technologies. The high, medium, and low ranges are determined by the approximate number of computers in the network—for example, high range indicates >106 computers in the network, medium is 106 to 103, and low is <103. dGeographical scope of the network: global, national, regional, or local. ePotential consequences for society at large of a failure that is extremely destructive yet highly improbable. High range means >$100 million and low means <$100 million.
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Network Science munications and information networks. The implications of this fact for criminal, terror, protest, and insurgency networks have been explored by Arquilla and Ronfeldt (2001) and are a common topic of discussion by groups like the Highlands Forum, which perceive that the United States is highly vulnerable to the interruption of critical networks. Finding 2-5. The high value attached to common engineered networks makes their design, scaling, and operation a topic of national priority. It seems self-evident from the ubiquity of networks in our daily lives, as well as from the potential for massive civil disruption if they fail, that the design, scaling, and operation of networks is a national priority. Failures and threats of failure caused by terrorist action add urgency to the strategic imperative to design, deploy, and operate robust networks whose behaviors are predictable. Yet as we shall see later in this report, fundamental (as opposed to empirical) knowledge about how to do this is primitive. The current state of knowledge about network design and characterization is roughly analogous to the state of knowledge about metallurgy in Europe in the 16th century. The empirical steel-forming technology of the day was sufficiently advanced to enable Europe to conquer most of the world but provided only a pale indication of the materials designs that would become possible in the 20th century based on the science of metallurgy (Diamond, 1999). As the committee looked at the current state of network technology and research in relation to our near total dependence on networks, it was amazed at the abundance of interest in network applications and the lack of fundamental scientific research that might advance the development of an underlying network science to support the study of networks in general. Finding 2-6. Interest in network research has exploded during the past 5 years. Research on networks has become highly visible during the past 5 years. A number of the measures that normally accompany the emergence of a new field document this heightened interest. For example, the number of publications focusing on complex networks increased significantly during that time. A “complex network” is one that exhibits emergent behaviors that cannot be predicted a priori from known properties of the network’s constituents (Boccara, 2004). This is not limited to a single discipline, but it is stimulated by simultaneous interest in communication systems (like the Internet or the Web), biological systems (like metabolic or protein interaction networks), and social systems (like collaboration or e-mail networks). As shown in Figure 2-1, the number of publications with “complex networks” in their title has increased fourfold over the past 5 years without signs of saturation. The two most cited papers on complex networks have been cited more than 1,500 times, according to Google Scholar (Watts and Strogatz, 1998; Barabási and Albert, 1999). Fueled by this increasing interest, major scientific journals have devoted special issues, reviews, or editorials to the promise of networks. For example, Nature has published several reviews on the subject (Strogatz, 2001; Ottino, 2004; Koonin et al., 2002). Science and the Proceedings of the National Academy of Sciences devoted special issues to it (Jasny and Ray, 2003; PNAS, 2004). Two major physics review journals, Reviews of Modern Physics and Advances in Physics, have each published highly cited reviews on networks (Albert and Barabási, 2002; Dorogovtsev and Mendes, 2002). So have major engineering, applied mathematics, and sociology journals, like IEEE Control Systems Magazine, SIAM Review, and Annual Review of Sociology (Amin, 2002; Watts, 2004; Newman, 2003). Furthermore, several of the most prominent biology journals, like Nature Reviews Genetics, Nature Immunology, Nature Structural Biology, and Nature Reviews Systems Biology, have published high-profile reviews and editorials, often highlighting them on the cover of the journal, as shown in Figure 2-2. Another sign of the emergence of a network science community is the organization of meetings devoted to network research. Indeed, during the past 5 years more than 20 international conferences and workshops and summer schools have focused exclusively on network research, some drawing close to 400 participants. Electrical engineering and computer science conferences have for many years devoted entire sessions to networks. In addition, major physics and biology meetings devote many focus sessions to networks. For example, the March 2004 and March 2005 meetings of
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Network Science FIGURE 2-1 Number of papers with the term “complex network” in the title. SOURCE: Introduction to Complex Networks: Modeling, Control and Synchronization. Briefing by Guanrong Chen, director, Centre for Chaos Control and Synchronization, City University of Hong Kong, to the First Chinese Conference on Complex Networks, Wuhan, China, April 2005. the American Physical Society (APS), the largest annual physics meeting in the world, had more than 10 network-related sessions. Similarly, the American Association for the Advancement of Science (AAAS) regularly features symposia devoted to network science and its applications. The number of books on network science has exploded. Four general-audience books, translated into over 10 languages and making the bestseller list in several countries, introduced the promise of network science to the general public (Barabási, 2002; Buchanan, 2002; Watts, 2003; Huberman, 2001). Box 2-1 also lists over 15 monographs focusing either on network science in general or on its applications to specific fields. In 2004, responding to the public’s fascination with networks, the New York Hall of Science opened a major exhibit entitled “Connections: Seeing the World in a Different Way.” The exhibit focused on the impact of networks on science, technology, and the arts. Finally, as is discussed in Chapter 5 and Appendix C, most major U.S. universities have developed courses on various aspects of network science. These are offered in a variety of departments, including electrical engineering, physics, computer science, biology, economics, and sociology. The European Union recognized the potential of research in networks early on under its Sixth Framework Program1 by investing several million euros per year in flagship programs, such as COSIN, EVERGROW, DELIS, and EXYSTENCE, which focus on complex networks and their applications (Amaral et al., 2004). In addition to providing the knowledge underlying the design and operation of many of the global communications, transportation, and power infrastructures noted in Tables 2-1 and 2-2, network research is leading to the creation of new businesses. The poster child of the benefits of network thinking is Google and all the second-generation search engines built after Google. Indeed, Google’s phenomenal success and what sets it apart from its early competitors is its revolutionary algorithm, which used the topology of the Web to rank the obtained search results. Google is a wonderful example of how a piece of published research by two graduate students on random walks on networks, an academic exercise, 1 For further information, see http://www.cordis.lu/ist/fet/co.htm. Accessed August 19, 2005.
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Network Science FIGURE 2-2 Magazines and journals with articles on networks. led in less than a decade to a multibillion-dollar company (Brinn and Page, 1998). Search engines are not the only new business spawned by network research. A rapidly evolving industry has developed around social networks. Products are developed based on information gleaned from mapping out people’s social links. The businesses range from facilitating business contacts to providing dating services. Some of the companies aim to revolutionize the sales process by identifying the shortest acquaintance path from a salesperson to a target person. In the past 3 years more than 20 companies have emerged that use some aspects of social networks to provide benefits to consumers. Small companies are springing up to apply an understanding of network structure to practical concerns. One example is the work by Internet Perils, Inc., to improve the robustness of a company’s Internet connectivity by identifying bottleneck hubs that lie on seemingly diverse paths. The interest in network research has resulted in a number of network analysis tools. The majority of these tools focus on network visualization; some are free, others can be purchased. In an intermediate time frame, biology is likely to benefit from advances in network research (Barabási and Oltvai, 2004), and a rush is on to capitalize on applications of the genomics revolution. It is increasingly apparent that the design of successful drugs for complex diseases like cancer or depression depends on mapping out the interactions between cell components. Several companies are involved in commercializing this mapping process, and developing tools that take advantage of network representations of a cell. For example, Genomatica, a San-Diego-based company, has developed a series of tools: Starting with knowledge of the structure of a metabolic network, Genomatica generates predictions useful in a range of ways, from developing drugs to developing strains of bacteria with special metabolic characteristics. All in all, the committee finds that research on networks not only underlies the affordability and reliability of the glo-
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Network Science BOX 2-1 Books Relevant to Network Science General Audience Albert-László Barabási, Linked: The New Science of Networks. Cambridge, Mass.: Perseus Publishing, 2002. Mark Buchanan, Nexus: Small Worlds and the Groundbreaking Science of Networks. New York, N.Y.: W.W. Norton, 2002. Bernardo A. Huberman, The Laws of the Web: Patterns in the Ecology of Information. Cambridge, Mass.: MIT Press, 2001. Duncan J. Watts, Six Degrees: The Science of a Connected Age. New York, N.Y.: W.W. Norton, 2003. Monograph and Proceedings Eli-Ben Naim, Hans Frauenfelder, and Zoltan Toroczkai, Complex Networks (Lecture Notes in Physics). Springer-Verlag, October 16, 2004. S.N. Dorogovtsev and J.F.F. Mendes, Evolution of Networks: From Biological Nets to the Internet and WWW. Oxford, England: Oxford University Press, 2003. S. Bornholdt and H.G. Schuster, eds., Handbook of Graphs and Networks: From the Genome to the Internet. Weinheim, Berlin: Wiley-VCH, 2003. Pedro L. Garrido and Joaquín Marro, eds., Modeling Complex Systems, Seventh Granada Lectures, Spain 2002. American Institute of Physics Conference Proceedings, Vol. 661. Melville, N.Y.: AIP, 2003. Duncan J. Watts, Small Worlds: The Dynamics of Networks Between Order and Randomness. Princeton, N.J.: Princeton University Press, 1991. Graph Theory/Algorithms Béla Bollobas, Random Graphs, 2nd Ed. Cambridge, England: Cambridge University Press, 2001. Clifford W. Marshall, Applied Graph Theory. New York, N.Y.: Wiley-Interscience, 1971. Joel Spencer, The Strange Logic of Random Graphs: Algorithms and Combinatorics. New York, N.Y.: Springer-Verlag, 2001. Internet/www Romualdo Pastor-Satorras and Alessandro Vespignani, Evolution and Structure of the Internet: A Statistical Physics Approach. Cambridge, England: Cambridge University Press, 2004. Pierre Baldi, Paolo Frasconi, and Padhraic Smyth, Modeling the Internet and the Web: Probabilistic Methods and Algorithms. England: John Wiley & Sons, 2003. Martin Dodge and Rob Kitchin, Mapping Cyberspace. New York, N.Y.: Routledge, 2001. Martin Dodge and Rob Kitchin, Atlas of Cyberspace. England: Addison-Wesley, 2001. Social Networks Stanley Wasserman and Katherine Faust, Social Network Analysis: Methods and Applications. Cambridge, England: Cambridge University Press, 1994, reprint 1999. Malcolm Gladwell, The Tipping Point: How Little Things Can Make a Big Difference. Boston, Mass.: Little, Brown and Company, 2000. Per Hage and Frank Harary, Island Networks: Communication, Kinship and Classification Structures in Oceania. Cambridge, England: Cambridge University Press, 1996. Manfred Kochen, The Small World. Norwood, N.J.: Ablex Publishing Corporation, 1989. R.R. McNeill and William H. McNeill, The Human Web: A Bird’s-Eye View of World History. New York, N.Y.: W.W. Norton, 2003. Peter R. Monge and Noshir S. Contractor, Theories of Communication Networks. New York, N.Y.: Oxford University Press, 2003. Wayne E. Baker, Networking Smart: How to Build Relationships for Personal and Organizational Success. Available online at http://Backinprint.com. Wayne E. Baker, Achieving Success Through Social Capital: Tapping Hidden Resources in Your Personal and Business Networks. Jossey-Bass, 2000. Economic Systems/Political Networks Manuel Castells, The Internet Galaxy. New York, N.Y.: Oxford University Press, 2001. Ross Dawson, Living Networks: Leasing your Company, Customers, and Partners in the Hyper-Connected Economy. Upper Saddle River, N.J.: Prentice Hall, 2003. Dirk Messner, The Network Society: Economic Development and International Competitiveness as Problems of Social Governance. Frank Cass Publishers, 1997. Chris Westland, Financial Dynamics: A System for Valuing Technology Companies. New York, N.Y.: John Wiley & Sons, 2003. Networks in the Arts and Culture Alistair Reynolds, “Glacier” in The Year’s Best Science Fiction 2001, Gardner Dozois, ed. New York, N.Y.: St. Martin’s Griffin, 2002. Mark Lombardi, Robert Hobbs, and Judith Richards, Mark Lombardi: Global Networks. Independent Curators, August 2003. Mark C. Taylor. The Moment of Complexity: Emerging Network Culture. Chicago, Ill.: University of Chicago Press, 2002. Other Books Discussing Various Aspects of Networks Fritjof Capra, The Web of Life: A New Scientific Understanding of Living Systems. New York, N.Y.: Anchor Books/Randomhouse, 1996. Geoff Mulgan, Connexity: How to Live in a Connected World. Cambridge, Mass.: Harvard Business School Press, 1998. Steven Strogatz, Sync: The Emerging Science of Spontaneous Order. New York, N.Y.: Hyperion, 2003. Judy Breck, Connectivity: The Answer to Ending Ignorance and Separation. Lanham, Md.: Rowman & Littlefield, 2004.
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Network Science bal communications, transportation, and power infrastructures but also is an important source of economic growth via the creation of new commercial endeavors. Finding 2-7. Recent network research is leading to new and growing businesses. In summary, human understanding of networks has the potential to play a vital role in the 21st century, which is witnessing the rise of the Connected Age. There is an enormous demand for information on how to design and operate large global networks in a robust, stable, and secure fashion. In subsequent chapters, the committee discusses the dearth of fundamental scientific knowledge that would ensure that outcome. In Chapter 3, the committee looks at the use of networks in the military, and the special attention given in the statement of task to their role in network-centric warfare. REFERENCES Albert, R., and A.L. Barabási. 2002. Statistical mechanics of complex networks. Reviews of Modern Physics 74(1): 47–97. Amaral, L.A.N., A. Barrat, A.L. Barabási, G. Caldarelli, P. De Los Rios, A. Erzan, B. Kahng, R. Mantegna, J.F.F. Mendes, R. Pastor-Satorras, and A. Vespignani. 2004. Virtual round table on ten leading questions for network research. The European Physical Journal B 38(2): 143–145. Amin, M. 2002. Modeling and control of complex interactive networks. IEEE Control Systems Magazine 22(1): 22–27. Arquilla, J., and D. Ronfeldt. 2001. Networks and Netwars. Santa Monica, Calif.: RAND. Barabási, A.L. 2002. Linked: The New Science of Networks: The Future of Terror, Crime, and Militancy. Cambridge, Mass.: Perseus. Barabási, A.L., and R. Albert. 1999. Emergence of scaling in random networks. Science 286(5439): 509–512. Barabási, A.L., and Z.N. Oltvai. 2004. Network biology: Understanding the cell’s functional organization. Nature Reviews: Genetics 5(2): 101–114. Boccara, N. 2004. Modeling Complex Systems. New York, N.Y.: Springer. Bower, J.M., and H. Bolouri. 2001. Computational Modeling of Genetic and Biochemical Networks . Cambridge, Mass.: MIT Press. Brinn, S., and L. Page. 1998. The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems 30(1–7): 107–117. Buchanan, M. 2002. Nexus: Small Worlds and the Groundbreaking Science of Networks. New York, N.Y.: W.W. Norton. Diamond, J. 1999. Guns, Germs and Steel: The Fates of Human Societies. New York, N.Y.: W.W. Norton. Dorogovtsev, S.N., and J.F.F. Mendes. 2002. Evolution of networks. Advances in Physics 51(4): 1079–1187. Dorogovtsev, S.N., and J.F.F. Mendes. 2003. Evolution of Networks: From Biological Nets to the Internet and WWW. Oxford, England: Oxford University Press. Huberman, B.A. 2001. The Laws of the Web: Patterns in the Ecology of Information. Cambridge, Mass.: MIT Press. Jasny, B.R., and L.B. Ray. 2003. Life and the art of networks. Science 301(5641): 1863. Koonin, E.V., Y.I. Wolf, and G.P. Karev. 2002. The structure of the protein universe and genome evolution. Nature 420(6912): 218–223. Newman, M.E.J. 2003. The structure and function of complex networks. SIAM Review 45(2): 167–256. Ottino, J.M. 2004. Engineering complex systems. Nature 427(6973): 399. Perez, C. 2002. Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages. Cheltenham, England: Edward Elgar Publishers. Proceedings of the National Academy of Sciences of the United States (PNAS). 2004. Mapping Knowledge Domains. 101(Suppl.1). Rheingold, H. 2002. Smart Mobs: The Next Social Revolution. Cambridge, Mass.: MA Basic Books. Strogatz, S. 2001. Exploring complex networks. Nature 410(6825): 268–276. Watts, D.J. 2003. Six Degrees: The Science of a Connected Age. New York, N.Y.: W.W. Norton. Watts, D.J. 2004. The “new” science of networks. Annual Review of Sociology 30(1): 243–270. Watts, D.J., and S. Strogatz. 1998. Collective dynamics of “small-world” networks. Nature 393(6684): 440–442.
Representative terms from entire chapter: