ISCOM links- Doug White

Information Society as a Complex System SFI Modena Course for Reggio, Dec 2003a

Irvine's new PhD program, now taking graduate student applications, in Social Dynamics and Evolution. This is a degree-granting Research Focus Group in the Mathematical Behavioral Sciences.

Networks of Trade

Structure and Dynamics of the Global Economy: Network Analysis of International Trade 1965-1980 David A. Smith, Douglas R. White Social Forces, Vol. 70, No. 4. (Jun., 1992), pp. 857-893.jstor

New Software and Results for regular equivalence (positional) analysis of input-output economic data and world trade

Thirteenth century world-system. A collaboration of Peter Spufford, Douglas White and Joseph Wehbe.

Theoretical background: Network Processes in Evolving Systems

Networks and Ethnography

Introduction: Networks, Ethnography and Emergence. Chapter 1 of Network Analysis and Ethnographic Problems, with Ulla Johansen.

Glossary: Analytical Concepts for Networks and Ethnography (for the book)

Bibliography (for the book) - covers alot of the new literature on networks

2002 Ulla Johansen and Douglas R. White, Collaborative Long-Term Ethnography and Longitudinal Social Analysis of a Nomadic Clan In Southeastern Turkey. Chapter 4, pp. 81-99, in Chronicling Cultures: Long-Term Field Research in Anthropology, edited by Robert van Kemper and Anya Royce. AltaMira Press.

2002 Douglas R. White and Michael Houseman The Navigability of Strong Ties: Small Worlds, Tie Strength and Network Topology, in Networks and Complexity Special Issue, Complexity 8(1):72-81. SFI Preprint eScholarship Reprint

Turkish Nomad Long-term study site

2003 Douglas R. White, Emergence, transformation and decay in pastoral nomad socio-natural systems. to appear in Emergence, Transformation and Decay in Socio-Natural Systems, edited by Sander van der Leeuw, Uno Svedin, Tim Kohler, and Dwight Read.

1997 Lilyan A. Brudner and Douglas R. White. Class, Property and Structural Endogamy: Visualizing Networked Histories Theory and Society 25:161-208.

Organizational Networks

2003 Douglas R. White. Social Scaling: From scale-free to stretched exponential models for scalar stress, hierarchy, levels and units in human and technological networks and evolution. ISCOM working paper, for submission to: Computer and Mathematical Organization Theory Download: PDF 1982scalingDRW.pdf

2004 Walter W. Powell, Douglas R. White, Kenneth W. Koput and Jason Owen-Smith. Network Dynamics and Field Evolution: The Growth of Interorganizational Collaboration in the Life Sciences. Forthcoming: American Journal of Sociology Download: PDF SFI-WP2003ajs.pdf

2003 Douglas R. White, Walter W. Powell, Jason Owen-Smith and James Moody Network Models and Organization Theory: from embeddedness to ridge structure. In preparation for Computational and Mathematical Organization Theory special issue on Mathematical Representations for the Analysis of Social Networks within and between Organizations, guest edited by Alessandro Lomi and Phillipa Pattison.

Link to the movie and graphics

2003 James Moody and Douglas R. White, Social Cohesion and Embeddedness: A Hierarchical Concept of Social Groups. American Sociological Review 68(1):1-25.

2001 Douglas R. White and Frank Harary, The Cohesiveness of Blocks in Social Networks: Node Connectivity and Conditional Density. Sociological Methodology 2001, vol. 31, no. 1, pp. 305-359. Blackwell Publishers, Inc., Boston, USA and Oxford, UK. SFI Posting

2003 Douglas R. White Network Analysis, Social Dynamics and Feedback in Social Systems. Cybernetics and Systems, online journal, forthcoming special issue. Edited by Dwight Read. Introduction by Murray Leaf

2003 Douglas R. White, Ties, Weak and Strong. Encyclopedia of Community Vol. 4:1376-1379. Edited by Karen Christensen and David Levinson. Thousand Oaks, CA: Sage Reference.

Analytic Methods

such as are in pdf (see: software) coef.for

A fortran program to compute expected clustering coefficient following Bollobás's formula (2003) Douglas R. White coef.for, coef.exe

Using Galois Lattices to Represent Network Data Linton C. Freeman, Douglas R. White Sociological Methodology, Vol. 23. (1993), pp. 127-146. jstor

Representing and Computing Kinship: A New Approach Douglas R. White, Paul Jorion Current Anthropology, Vol. 33, No. 4. (Aug. - Oct., 1992), pp. 454-463. jstor

1999 On-line Controlled Simulation of Marriage Systems: J.Artificial Societies & Social Simulation 2(3)


Network Scaling

New Book: Handbook_of_Graphs_and_Networks.pdf scan

The degree sequence of a scale-free random graph process B. Bollobas, O. Riordan, G. Tusnary and J. Spencer. Random Structures and Algorithms, vol 18, 2001, 279-290.
Description: In modelling the web graph new vertices are joined to old vertices in proportion (maybe!) to the current degrees of the old vertices so that the rich get richer. Analyzing this process leads to some intriguing power laws.

Linearized chord diagrams and an upper bound for vassiliev invariants Béla Bollobás and Oliver Riordan, Journal of Knot Theory and Its Ramifications, Vol. 9, No. 7 (2000) 847-853

Luis Bettencourt and David I. Kaiser QUIKTIME Graphing the [Feynman] Graphers: how are ideas created and how they spread; An example from the history of Theoretical Physics
N.B. this file is too big to run on the web so right click and copy to your directory and open from there!!!

Johnson, Gregory 1982 Organizational Structure and Scalar Stress This pdf was made from scanned versions - if you are dubious about the accuracy of the scan, check the following: GAJ7-12.pdf GAJ7-12.pdf GAJ13-17.pdf . In Theory and Explanation in Archaeology: The Southampton Conference, Colin Renfrew, Michael Rowlands and Barbara A. Segraves-Whallon, Editors pp. 397-421. Academic Press. (mentioned in Sander's talk)

1978 Johnson, Gregory Information Sources and the Development of Decision-Making Organizations. In Social Archaeology: Beyond Subsistence and Dating, Redman, C.L. 87-112. New York: Academic Press, 1978. file is huge so download first and then print

Two that cite Johnson: a paper by Tim Kohler

Ecology, Group Formation and Group Size as factors of Coalitional Psychology By Eric Schniter

An important counter to the claim that scale-free networks arise only by growth processes: A steady state model for graph power laws pdf David Eppstein, Joseph Wang Abstract: Power law distribution seems to be an important characteristic of web graphs. Several existing web graph models generate power law graphs by adding new vertices and non-uniform edge connectivities to existing graphs. Researchers have conjectured that preferential connectivity and incremental growth are both required for the power law distribution. In this paper, we propose a different web graph model with power law distribution that does not require incremental growth. We also provide a comparison of our model with several others in their ability to predict web graph clustering behavior.

EppsteinPowerLawGenerator Scott White, JUNG programming system in java (see Tim Evans email)


EppsteinPowerLawGenerator Scott White, JUNG programming system in java (see Tim Evans email)

Luis Bettencourt Tipping the balances of a small world

From boom to bust and back again: the complex dynamics of trends and fashions

Biological Scaling

General Models of Biological Scaling

links to bibliography of Scaling

Re-examination of the 3/4 law of metabolism, Dodds, Rothman, Weitz. Journal of Theoretical Biology 209 (2001)

Other Scaling Papers

social organization and scaling SFI talk by Luis Bettencourt

Scale-free and hierarchical structures in complex networks Barabasi, Dezso, Ravasz, Yook and Oltvai

A Random Graph Model for Massive GraphsAiello, Chung, and Lu

The Small-World of Human Language Ramon Ferrer and Ricard V. Sole Proc. Roy. Soc. London B 268 (2001) 2261-2266

Scale-Free Behavior in Protein Domain Networks Stefan Wuchty
Orthologous enrichment in protein netwo Wuchty et al
2002 S. Wuchty, "Interaction and Domain Networks of Yeast", Proteomics, 2(12), 1715-1723 [pdf]
2003 S. Wuchty, "Small-Worlds in RNA", Nucl. Acids Res., 31, 1108 - 1117 [pdf]
2003 S. Wuchty and P.F. Stadler, "Centers of large networks", J. theoret. Biol., 223, 45-53 [pdf]

The large-scale organization of metabolic networks (2000)

Growth dynamics of the World-Wide LA Adamic and BA Huberman

Small World patterns in Food Webs Montoya and Sole

Food web complexity and higher-level ecosystem services

(very very partial start for articles)-please contribute

Field Theory for Networks

Why social networks are different from other types of networks 2003 M. E. J. Newman, Juyong Park. Condensed Matter, abstract
Degree correlation: the product of nodal degree multiplied by excess or deficit of observed over expected edge frequency, i.e., that hubs tend to connect. Negative degree correlation occurs when hub-to-hub connection is avoided and hubs tend to connect to nodes with low degree. Note that positive degree correlation k-cone connectivity ought to correlate.

references sent to the group in early OCTOBER 2003

[1]Jean Laherrère, D. Sornette. 1998. Stretched exponential distributions in Nature and Economy: ``Fat tails'' with characteristic scales. Eur.Phys.J. B2: 525-539.

[2] U. Frisch, D. Sornette 1997. Extreme deviations and applications J. Phys. I France 7, 1155-1171.

[3] D. Sornette. 1998. Multiplicative processes and power laws. Phys. Rev. E 57 N4, 4811-4813.

[4] A.V. Goltsev, S.N. Dorogovtsev, J.F.F. Mendes. 2003. Critical phenomena in networks Phys. Rev. E 67, 026123.

[5] M. Mitzenmacher. 2001. A Brief History of Generative Models for Power Law and Lognormal Distributions. Internet Miathematics

Evolution of Networks Dorogovtsev: USEFUL PAPERS ON NETWORKS. overview BOOK: S.N. Dorogovtsev and J.F.F. Mendes, Evolution of Networks: From Biological Nets to the Internet and WWW, Oxford University Press, Oxford, ISBN: 0198515901, 31 January 2003, 288 pp., 117 line illus. Synopsis: This text provides a concise, informative introduction to the principles of the organization and evolution of both natural and artificial networks. These are new concepts, based on the latest progress in network science. The book is written by physicists and is addressed to all researchers involved in the field and students. The aim of the text is to understand the generic principles of the complex organization of diverse networks: the Internet and World Wide Web, cellular networks, social nets, and many others. The ideas are presented in a clear and a pedagogical way, with minimal mathematics, so even students without a deep knowledge of mathematics and statistical physics will be able to rely on this as a reference. Special attention is given to real networks. Collected empirical data and numerous real applications of existing concepts are discussed in detail, as well as the topical problems of communication and other networks.

Biology-Inspired techniques for Self-Organization in dynamic Networks Bologna, SFI, EU


Complex Real-World Networks European Physical Society meeting, 2002