Thesis: Bibliography

Aboud, F. E., Mendelson, M. J., 1996. Determinants of friendship selection and quality: Developmental perspectives. In: Bukowski, W. M., Newcomb, A., Hartup, W. W. (Eds.), The Company They Keep: Friendship in Childhood and Adolescence. Cambridge University Press, New York, NY, pp. 87-112.

Ahuja, G., 2000. Collaborative networks, structural holes, and innovation: a longitudinal study. Administrative Science Quarterly 45, 425-455.

Albert, R., Jeong, H., Barabasi, A. L., 1999. Diameter of the world-wide web. Nature 401, 130-131.

Amaral, L. A. N., Guimera, R., 2006. Complex networks: Lies, damned lies and statistics. Nature Physics 2, 75-76.

Amaral, L. A. N., Scala, A., Barthelemy, M., Stanley, H. E., 2000. Classes of smallworld networks. Proceedings of the National Academy of Sciences 97, 11149- 11152.

Ash, G., 1997. Dynamic Routing in Telecommunication Networks. McGraw-Hill, New York, NY.

Balcan, D., Erzan, A., 2007. Content-based networks: A pedagogical overview. Chaos 17 (026108).

Barabasi, A.-L., Albert, R., 1999. Emergence of scaling in random networks. Science 286, 509-512.

Barabasi, A.-L., Jeonga, H., Neda, Z., Ravasz, E., Schubert, A., Vicsek, T., 2002. Evolution of the social network of scientific collaborations. Physica A 311, 590- 614.

Barrat, A., Barthelemy, M., Pastor-Satorras, R., Vespignani, A., 2004. The architecture of complex weighted networks. Proceedings of the National Academy of Sciences 101 (11), 3747-3752.

Batagelj, V., Mrvar, A., 2007. Pajek: Program for Large Network Analysis: version 1.20. http://vlado.fmf.uni-lj.si/pub/networks/pajek/.

Bernard, H. R., Killworth, P. D., Kronenfeld, D., Sailer, L. D., 1984. The problem of informant accuracy: the validity of retrospective data. Annual Review of Anthropology 13, 495-517.

Bernard, H. R., Kilworth, P. D., Evans, M. J., McCarty, C., Selley, G. A., 1988. Studying social relations cross-culturally. Ethnology 27 (2), 155-179.

Bollobas, B., 1998. Modern Graph Theory. Springer, New York, NY.

Boost Library developers, 2008. Boost Library. http://www.boost.org.

Borgatti, S. P., Carley, K., Krackhardt, D., 2006. Robustness of centrality measures under conditions of imperfect data. Social Networks 28 (2), 124-136.

Borgatti, S. P., Everett, M. G., Freeman, L. C., 2002. Ucinet for Windows: Software for Social Network Analysis. Analytic Technologies, Harvard, MA.

Breslow, N. E., 1996. Statistics in epidemiology: The case-control study. Journal of the American Statistical Association 91 (433), 14-28.

Broder, A., Kumar, R., Maghoul, F., Raghavan, P., Rajagopalan, S., Stata, R., Romkins, A., Wiener, J., 2000. Graph Structure of the Web. Preprint IBM Almaden.

Burt, R. S., 1992. Structural Holes: The Social Structure of Competition. Harvard University Press, Cambridge, MA.

Burt, R. S., 2005. Brokerage and Closure. An Introduction to Social Capital. Oxford University Press, New York, NY.

Burt, R. S., Lin, N., 1977. Network time series from archival records. Sociological Methodology 8, 224-254.

Butts, C. T., 2006. sna-package: Package for Social Network Analysis. R package version 1.4.

Butts, C. T., Handcock, M. S., Hunter, D. R., 2008. network: Classes for Relational Data. http://statnet.org/.

Caldarelli, G., 2007. Scale-Free Networks: ComplexWebs in Nature and Technology. Oxford University Press, Oxford, UK.

Coleman, J. S., 1988. Social capital in the creation of human capital. American Journal of Sociology 94, S95-S120.

Colizza, V., Flammini, A., Serrano, M. A., Vespignani, A., 2006. Detecting rich-club ordering in complex networks. Nature Physics 2, 110-115.

Cosslett, S. R., 1981. Ecient estimation of discrete-choice models. In: Manski, C. F., McFadden, D. (Eds.), Structural Analysis of Discrete Data with Econometric Applications. MIT Press, Cambridge, MA, pp. 467-492.

Cox, D. R., Hinkley, D. V., 1974. Theoretical Statistics. Chapman & Hall, London, UK.

Cross, R., Parker, A., 2004. The Hidden Power of Social Networks. Harvard Business School Press, Boston, MA.

Davis, J. A., 1970. Clustering and hierarchy in interpersonal relations: Testing two graph theoretical models on 742 sociomatrices. American Sociological Review 35 (5), 843-851.

De Masi, G., Iori, G., Caldarelli, G., 2006. Fitness model for the italian interbank money market. Physical Review E 74 (066112).

Dijkstra, E. W., 1959. A note on two problems in connexion with graphs. Numerische Mathematik 1, 269-271.

Doreian, P., 1969. A note on the detection of cliques in valued graphs. Sociometry 32 (2), 237-242.

Dorogovtsev, S. N., Mendes, J. F. F., 2003. Evolution of Networks. From Biological Nets to the Internet and WWW. Oxford University Press, New York, NY.

Drucker, P. F., 1993. The Post-Capitalist Society. HarperBusiness, New York, NY.

Ebel, H., Mielsch, L.-I., Bornholdt, S., 2002. Scale-free topology of e-mail networks. Physical Review E 66, 035103.

Erdos, P., Renyi, A., 1959. On random graphs. Publicationes Mathematicae 6, 290- 297.

Erdos, P., Renyi, A., 1960. On the evolution of random graphs. Publications of the Mathematical Institute of the Hungarian Academy of Sciences 5, 17-61.

Fararo, T. J., Sunshine, M., 1964. A Study of a Biased Friendship Network. Syracuse University Press, Syracuse, NY.

Feld, S. L., 1981. The focused organization of social ties. American Journal of Sociology 86, 1015-1035.

Fisek, H., Norman, R., Nelson-Kilger, M., 1992. Status characteristics and expectation states theory: a priori model parameters and test. Journal of Mathematical Sociology 16 (4), 285-303.

Foster, C. C., Rapoport, A., Orwant, C. J., 1963. A study of a large sociogram: Elimination of free parameters. Behavioural Science 8, 56-65.

Frank, O., Strauss, D., 1986. Markov graphs. Journal of the American Statistical Association 81, 832-842.

Freeman, L. C., 1978. Centrality in social networks: Conceptual clarification. Social Networks 1, 215-239.

Freeman, L. C., 1992. The sociological concept of “group”: An empirical test of two models. American Journal of Sociology 98 (1), 152-166.

Freeman, L. C., 2004. The Development of Social Network Analysis: A Study in the Sociology of Science. BookSurge, North Charleston, SC.

Freeman, L. C., Borgatti, S. P., White, D. R., 1991. Centrality in valued graphs: A measure of betweenness based on network flow. Social Networks 13 (2), 141-154.

Friedkin, N. E., 1984. Structural cohesion and equivalence explanations of social homogeneiety. Sociological Methods and Research 12, 235-261.

Gouldner, A. W., 1960. The norm of reciprocity: A preliminary statement. American Sociological Review 25 (2), 161-178.

Granovetter, M., 1973. The strength of weak ties. American Journal of Sociology 78, 1360-1380.

Guimera, R., Mossa, S., Turtschi, A., Amaral, L. A. N., 2005. The worldwide air transportation network: Anomalous centrality, community structure, and cities’ global roles. Proceedings of the National Academy of Sciences 102, 7794-7799.

Guimera, R., Sales-Pardo, M., Amaral, L. A. N., 2007. Classes of complex networks defined by role-to-role connectivity profiles. Nature Physics 3, 63-69.

Gulati, R., Gargiulo, M., 1999. Where do interorganizational networks come from. American Journal of Sociology 104, 1439-1493.

Hall, B. H., Jaffe, A. B., Tratjenberg, M., 2001. The NBER patent citations data file: Lessons, insights, and methodological tools. NBER Working Paper No. 8498.

Hallinan, M. T., 1974. A structural model of sentiment relations. American Journal of Sociology 80, 364-378.

Hallinan, M. T., Kubitschek, W. N., 1988. The effects of individual and structural characteristics on intransitivity in social networks. Social Psychology Quarterly 51, 81-92.

Handcock, M. S., 2003. Statistical models for social networks: degeneracy and inference. In: Breiger, R., Carley, K. M., Pattison, P. E. (Eds.), Dynamic Social Network Modeling and Analysis. National Academies Press, Washington, DC, pp. 229-240.

Handcock, M. S., Hunter, D. R., Butts, C. T., Goodreau, S. M., Morris, M., 2003. statnet: Software Tools for the Statistical Modeling of Network Data. http://statnetproject.org.

Hansen, M. T., 1999. The search-transfer problem: The role of weak ties in sharing knowledge across organization subunits. Administrative Science Quarterly 44, 232-248.

Harris, R. G., 2001. The knowledge-based economy: intellectual origins and new economic perspectives. International Journal of Management Reviews 3, 21-40.

Heider, F., 1946. Attitudes and cognitive organization. Journal of Psychology 21, 107-112.

Hinds, P. J., Carley, K. M., Krackhardt, D., Wholey, D., 2000. Choosing work group members: Balancing similarity, competence, and familiarity. Organizational Behavior and Human Decision Processes 81 (2), 226-251.

Hinds, P. J., Kiesler, S., 1995. Communication across boundaries: Work, structure, and use of communication technologies in a large organization. Organization Science 6 (4), 373-393.

Holland, P. W., Leinhardt, S., 1970. A method for detecting structure in sociometric data. American Journal of Sociology 76, 492-513.

Holland, P. W., Leinhardt, S., 1971. Transitivity in structural models of small groups. Comparative Group Studies 2, 107-124.

Holland, P. W., Leinhardt, S., 1981. An exponential family of probability distributions for directed graphs. Journal of the American Statistical Association 76, 33-65.

Holme, P., Edling, C. R., Liljeros, F., 2004. Structure and time-evolution of an internet dating community. Social Networks 26, 155-174.

Hosmer, D. W., Lemeshow, S., 2000. Applied Logisitc Regression, 2nd ed. John Wiley & Sons, New York, NY.

Hunter, D. R., Goodreau, S. M., Handcock, M. S., 2008. Goodness of fit of social network models. Journal of the American Statistical Association 103, 248-258.

Jeong, H., Neda, Z., Barabasi, A.-L., 2003. Measuring preferential attachment for evolving networks. Europhysics Letters 61, 567-572.

Kalmijn, M., Flap, H., 2001. Assortative meeting and mating: Unintended consequences of organized settings for partner choices. Social Forces 79 (4), 1289-1312.

Karlberg, M., 1997. Testing transitivity in graphs. Social Networks 19 (4), 325-343.

Karlberg, M., 1999. Testing transitivity in digraphs. Sociological Methodology 29, 225-251.

Katz, L., 1953. A new status index derived from sociometric analysis. Psychometrika 18, 39-43.

Katz, L., Proctor, C. H., 1959. The configuration of interpersonal relations in a group as a time-dependent stochastic process. Psychometrika 24, 253-287.

King, G., Zeng, L., 2001. Logistic regression in rare events data. Political Analysis 9 (2), 137-163.

Korte, C., Milgram, S., 1970. Acquaintance linking between white and negro populations: application of the small world problem. Journal of Personality and Social Psychology 15, 101-108.

Kossinets, G., Watts, D. J., 2006. Empirical analysis of an evolving social network. Science 311, 88-90.

Krackhardt, D., 1992. The strength of strong ties: The importance of philos in organizations. In: Nohria, N., Eccles, R. (Eds.), Networks and Organizations: Structure, Form, and Action. Harvard Business School Press, Boston MA, pp. 216-239.

Lazarsfeld, P. F., Merton, R. K., 1954. Friendship as social process: A substantive and methodological analysis. In: Berger, M., Abel, T., Page, C. (Eds.), Freedom and Control in Modern Society. Van Nostrand, New York, NY, pp. 18-66.

Lazega, E., 2001. The Collegial Phenomenon: The Social Mechanisms of Cooperation Among Peers in a Corporate Law Partnership. Oxford University Press, Oxford, UK.

Leskovec, J., Kleinberg, J., Faloutsos, C., 2005. Graphs over time: Densification laws, shrinking diameters and possible explanations. Proceedings of the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.

Levin, D. Z., Cross, R., 2004. The strength of weak ties you can trust: The mediating role of trust in effective knowledge transfer. Management Science 50 (11), 1477- 1490.

Long, J. S., Freese, J., 2003. Regression Models for Categorical Dependent Variables using Stata, rev. ed. Stata Press, College Station, TX.

Louch, H., 2000. Personal network integration: Transitivity and homophily in strong-tie relations. Social Networks 22, 45-64.

Luce, R. D., Perry, A. D., 1949. A method of matrix analysis of group structure. Psychometrika 14 (1), 95-116.

Luczkowich, J. J., Borgatti, S. P., Johnson, J. C., Everett, M. G., 2003. Defining and measuring trophic role similarity in food webs using regular equivalence. Journal of Theoretical Biology 220, 303321.

Lumley, T., 2008. survival: Survival analysis, including penalised likelihood. http://cran.r-project.org/web/packages/survival/.

Marsden, P. V., 1990. Network data and measurement. Annual Review of Sociology 16, 435-463.

Maslov, S., Sneppen, K., 2002. Specificity and stability in topology of protein networks. Science 296, 910-913.

MathWorks, Inc., 2007. Matlab Software: Version 7.4 (2007a). Natick, MA.

Matthew, 25:29. The Bible. BibleGateway.com: English Standard Version.

McFadden, D., 1973. Conditional logit analysis of qualitative choice behavior. In: Zarembka, P. (Ed.), Structural Analysis of Discrete Data: with Econometric Applications. MIT Press, Cambridge, MA, pp. 197-272.

McPherson, J. M., Smith-Lovin, L., Cook, J. M., 2001. Birds of a feather: Homophily in social networks. Annual Review of Sociology 27, 415-444.

Merton, R. K., 1968. The Matthew effect in science. Science 159, 56-63.

Milgram, S., 1967. The small world problem. Psychology Today 2, 60-67.

Molloy, M., Reed, B., 1995. A critical point for random graphs with a given degree sequence. Random Structures and Algorithms 6, 161-180.

Monge, P., Rothman, L., Eisenberg, E., Miller, K., Kirste, K., 1985. The dynamics of organizational proximity. Management Science 31, 1129-1141.

Mood, A. M., Graybill, F. A., Boes, D. C., 1974. Introduction to the Theory of Statistics, 3rd ed. McGraw-Hill, Singapore.

Moody, J., 2004. The structure of social science collaboration network: Disciplinary cohesion from 1963 to 1999. American Sociological Review 69, 213-238.

Moreno, J. L., 1938. Who Shall Survive? Foundations of Sociometry, Group Psychotherapy, and Sociodrama. Nervous and Mental Disease Publishing Co., Washington, DC.

Newman, M. E. J., 2001a. Clustering and preferential attachment in growing networks. Physical Review E 64, 016131.

Newman, M. E. J., 2001b. Scientific collaboration networks: I. Network construction and fundamental results. Physical Review E 64, 016131.

Newman, M. E. J., 2001c. Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. Physical Review E 64, 016132.

Newman, M. E. J., 2001d. The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences 98, 404-409.

Newman, M. E. J., 2003. The structure and function of complex networks. SIAM Review 45, 167-256.

Newman, M. E. J., 2004a. Analysis of weighted networks. Physical Review E 70, 056131.

Newman, M. E. J., 2004b. Who is the best connected scientist? A study of scientific coauthorship networks. In: Ben-Naim, E., Frauenfelder, H., Toroczkai, Z. (Eds.), Complex Networks. Springer, Berlin, Germany, p. 337370.

Newman, M. E. J., 2006. Finding community structure in networks using the eigenvectors of matrices. Physical Review E 76 (036104).

Newman, M. E. J., Park, J., 2003. Why social networks are different from other types of networks. Physical Review E 68, 036122.

Nordlund, C., 2007. Identifying regular blocks in valued networks: A heuristic applied to the St. Marks carbon flow data, and international trade in cereal products. Social Networks 29 (1), 59-69.

Onnela, J.-P., Saramki, J., Hyvnen, J., Szab, G., Lazer, D., Kaski, K., Kertsz, J., Barabasi, A.-L., 2007. Structure and tie strengths in mobile communication networks. Proceedings of the National Academy of Sciences 104, 7332-7336.

Opsahl, T., 2008. tnet: Software for Analysis of Weighted and Longitudinal networks, version 0.1.0.

Opsahl, T., Colizza, V., Panzarasa, P., Ramasco, J. J., 2008. Prominence and control: The weighted rich-club effect. Physical Review Letters 101 (168702).

Opsahl, T., Panzarasa, P., 2008. Mechanisms of network dynamics: Theoretical framework and methodological considerations. Proceedings of the 4th UK Social Network Conference University of Greenwich.

Opsahl, T., Panzarasa, P., 2009. Clustering in weighted networks. Social Networks 31 (2), 155-163.

Panzarasa, P., Opsahl, T., 2007. Scientific collaborations in business and management: The effects of network structure on research performance. Proceedings of the 2007 Annual Meeting of the Academy of Management Philadelphia, PA.

Panzarasa, P., Opsahl, T., Carley, K. M., 2009. Patterns and dynamics of users’ behavior and interaction: Network analysis of an online community. Journal of the American Society for Information Science and Technology 60 (5), 911-932.

Pareto, V., 1897. Cours d’economie politique. Macmillan, Paris, France.

Pastides, H., Kelsey, J. L., LiVolsi, V. A., Holford, T., Fischer, D., Goldberg, I., 1983. Oral contraceptive use and fibrocystic breast disease with special reference to its histopathology. Journal of the National Cancer Institute 71, 5-9.

Pastor-Satorras, R., Vespignani, A., 2004. Evolution and Structure of the Internet. Cambridge University Press, New York, NY.

Pattison, P. E., Wasserman, S., 1999. Logit models and logistic regressions for social networks. II. Multivariate relations. British Journal of Mathematical and Statistical Psychology 52, 169-194.

Pearson, M., Michell, L., 2000. Smoke rings: Social network analysis of friendship groups, smoking, and drug-taking. Drugs: Education, Prevention and Policy 7 (1), 21-37.

Pearson, M., West, P., 2003. Drifting smoke rings: Social network analysis and markov processes in a longitudinal study of friendship groups and risk-taking. Connections 25 (2), 59-76.

Peay, E. R., 1980. Connectedness in a general model for valued networks. Social Networks 2, 385-410.

Plickert, G., Cote, R. R., Wellman, B., 2007. It’s not who you know, it’s how you know them: Who exchanges what with whom? Social Networks 29, 405-429.

Powell, W. W., White, D., Koput, K. W., Owen-Smith, J., 2005. Network dynamics and field evolution: The growth of interorganizational collaboration in the life sciences. American Journal of Sociology 110 (4), 1132-1205.

R Development Team, 2008. R: Version 2.7. R Foundation for Statistical Computing, Vienna, Austria.

Ramasco, J. J., 2007. Social inertia and diversity in collaboration networks. European Physical Journal ST 143, 47-50.

Ramasco, J. J., Goncalves, B., 2007. Transport on weighted networks: when the correlations are independent of the degree. Physical Review E 76 (066106).

Ramasco, J. J., Morris, S., 2006. Social inertia in collaboration networks. Physical Review E 73 (016122).

Rao, A. R., Jana, R., Bandyopadhyay, S., 1996. A markov chain monte carlo method for generating random (0, 1)-matrices with given marginals. Sankhya A 58, 225- 242.

Rapaport, A., 1953. Spread of information through a population with sociostructural bias. I. Assumption of transitivity. Bulletin of Mathematical Biophysics 15, 523-533.

Reagans, R., McEvily, B., 2003. Network structure and knowledge transfer: The effects of cohesion and range. Administrative Science Quarterly 48, 240-267.

Robins, G. L., Morris, M., 2007. Advances in exponential random graph (p*) models. Social Networks 29 (2), 169-172.

Robins, G. L., Pattison, P. E., 2001. Random graph models for temporal processes in social networks. Journal of Mathematical Sociology 25, 5-41.

Robins, G. L., Snijders, T. A. B.,Wang, P., Handcock, M., Pattison, P., 2007. Recent developments in exponential random graph (p*) models for social networks. Social Networks 29 (2), 192-215.

Robins, G. L., Woolcock, J., Pattison, P. E., 2005. Small and other worlds: Global network structures from local processes. American Journal of Sociology 110, 894- 936.

Scott, J., 2000. Social Network Analysis: A Handbook. Sage Publications, London, UK.

Serrano, M. A., 2008. Rich-club vs rich-multipolarization phenomena in weighted networks. Physical Review E 78 (026101).

Serrano, M. A., Boguna, M., Vespignani, A., 2007. Patterns of dominant flows in the world trade web. Journal of Economic Interaction and Coordination 2, 111-124.

Simmel, G., 1950. The Sociology of Georg Simmel (KH Wolff, trans.). Free Press, New York, NY.

Simon, H. A., 1955. On a class of skew distribution functions. Biometrika 42, 425- 440.

Skvoretz, J., 2002. Complexity theory and models for social networks. Complexity 8, 47-55.

Snijders, T. A. B., 2001. The statistical evaluation of social network dynamics. Sociological Methodology 31, 361-395.

Snijders, T. A. B., 2002. Markov chain monte carlo estimation of exponential random graph models. Journal of Social Structure 3 (2), 361-395.

Snijders, T. A. B., Pattison, P. E., Robins, G. L., Handcock, M. S., 2006. New specifications for exponential random graph models. Sociological Methodology 35, 99-153.

Snijders, T. A. B., Steglich, C. E. G., 2008. Models for analyzing dynamics of valued networks. Proceedings of the 4th UK Social Networks conference, University of Greenwich, Greenwich, UK.

Snijders, T. A. B., Steglich, C. E. G., Schweinberger, M., Huisman, M., 2007. SIENA: version 3.1. University of Groningen: ICS / Department of Sociology; University of Oxford: Department of Statistics.

Snijders, T. A. B., Steglich, C. E. G., van de Bunt, G. G., 2008. Introduction to actor-based models for network dynamics. Unpublished manuscript, available at http://stat.gamma.rug.nl/siena articles.htm.

Soffer, S. N., Vzquez, A., 2005. Network clustering coecient without degreecorrelation biases. Physical Review E 71 (057101).

Solomonoff, R., Rapoport, A., 1951. Connectivity of random nets. Bulletin of Mathematical Biophysics 13, 107-117.

Sorenson, O., Stuart, T. E., 2001. Syndication networks and the spatial distribution of venture capital investments. American Journal of Sociology 106 (6), 1546-1588.

StataCorp, 2007. Stata Statistical Software: Release 10. StataCorp LP, College Station, TX.

Steglich, C. E. G., Snijders, T. A. B., Pearson, M., 2007. Dynamic networks and behavior: Separating selection from influence. Unpublished manuscript, available at http://stat.gamma.rug.nl/siena_articles.htm.

Travers, J., Milgram, S., 1969. An experimental study of the small world problem. Sociometry 32, 425-443.

Uetz, P., Giot, L., Cagney, G., Mansfield, T. A., Judson, R. S., Knight, J. R., Lockshon, D., Narayan, V., Srinivasan, M., Pochart, P., Qureshi-Emili, A., Li, Y., Godwin, B., Conover, D., Kalbeisch, T., Vijayadamodar, G., Yang, M., Johnston, M., Fields, S., Rothberg, J. M., 2000. A comprehensive analysis of protein-protein interactions in saccharomyces cerevisiae. Nature 403, 623-627.

Uzzi, B., 1997. Social structure and competition in interfirm networks: The paradox of embeddedness. Administrative Science Quarterly 42, 35-67.

Uzzi, B., Lancaster, R., 2004. Embeddedness and price formation in the corporate law market. American Sociological Review 69, 319-344.

Uzzi, B., Spiro, J., 2005. Collaboration and creativity: The small world problem. American Journal of Sociology 111, 447-504.

Valente, T., 1995. Network Models of the Diffusion of Innovations. Hampton Press, Cresskill, NJ.

Wang, P., Robins, G. L., Pattison, P. E., 2005. PNET: version 1.0. University of Melbourne, Melbourne, Australia.

Wasserman, S., Faust, K., 1994. Social Network Analysis. Cambridge University Press, Cambridge, MA.

Wasserman, S., Pattison, P. E., 1996. Logit models and logistic regression for social networks: I. An introduction to markov graphs and p*. Psychometrika 61, 401- 425.

Watts, D. J., 1999. Small Worlds. Princeton University Press, Princeton, NJ.

Watts, D. J., 2004. The “new” science of networks. Annual Review of Sociology 30, 243-270.

Watts, D. J., Strogatz, S. H., 1998. Collective dynamics of “small-world” networks. Nature 393, 440-442.

Wellman, B., 1999. Living networked on and offline. Contemporary Sociology 28 (6), 648-654.

Wu, Z., Braunstein, L. A., Colizza, V., Cohen, R., Havlin, S., Stanley, H. E., 2006. Optimal paths in complex networks with correlated weights: The world-wide airport network. Physical Review E 74 (056104).

Wuchty, S., 2007. Rich-club phenomenon in the interactome of p. falciparum-artifact or signature of a parasitic life style? PLoS ONE 2007 (e355).

Yang, S., Knoke, D., 2001. Optimal connections: strength and distance in valued graphs. Social Networks 23, 285-295.

Zhou, S., Mondragon, R. J., 2004. The rich-club phenomenon in the internet topology. IEEE Communications Letters, 8, 180-182.

Zipf, G. K., 1935. The Psycho-Biology of Language: An introduction to dynamic philology. Houghton Mifflin, Boston, MA.

Zlatic, V., Bianconi, G., Diaz-Guilera, A., Garlaschelli, D., Rao, F., Caldarelli, G., 2008. On the rich-club effect in dense and weighted networks. arXiv:0807.0793.