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Network Dynamics in Social and Economical Systems Cesar A. Hidalgo R. 1 Carlos Rodriguez-Sickert 2, A.-L. Barabasi 1 1 CCNR University of Notre Dame, Notre.

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Presentation on theme: "Network Dynamics in Social and Economical Systems Cesar A. Hidalgo R. 1 Carlos Rodriguez-Sickert 2, A.-L. Barabasi 1 1 CCNR University of Notre Dame, Notre."— Presentation transcript:

1 Network Dynamics in Social and Economical Systems Cesar A. Hidalgo R. 1 Carlos Rodriguez-Sickert 2, A.-L. Barabasi 1 1 CCNR University of Notre Dame, Notre Dame, IN 2Dept. of Sociology Pontificia Universidad Catolica de Chile Ann Arbor April 2007

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4 Core-Periphery structure The Stability of core and peripheral networks over time. David L. Morgan, Margaret B. Neal and Paula Carder, Social Networks 19 (1996) 9-25 234 widows, 1 year, 7 panels

5 Core = Kin The Stability of core and peripheral networks over time. David L. Morgan, Margaret B. Neal and Paula Carder, Social Networks 19 (1996) 9-25

6 Another More Recent Support study Relational Instability at the Network Core: Support Dynamics in developmental networks. Jonathon N. Cummings, Monica C. Higgins, Social Networks 28 (2006) 38-55 They analyzed 77 MBA graduates for 3 time periods and add relational content. The generating question was to name people that have taken an active interest and concerted action in the advancement of their careers. The conclusion is that the ties that granted psychosocial support compromised the inner core.

7 Yet Another Study 42 Women Re-entering college. Main Conclusion is that people for work support becomes more educated as this women get educated. Once a friend, always a friend? Effects of homophily on womens support networks accross a decade. Jill Suitor, Shirley Keeton, Social Networks 19 (1997) 51-62

8 Status Transition

9 Decay Functions [1] Decay Functions. Ronald S.Burt, Social Networks 22 (2000) 1-28.

10 Bridge Decay Bridge Decay. Ronald S. Burt, Social Networks 24 (2002) 333-363

11 The Persistence of Social Ties

12 Where? Western Country (Penetration >100%) Share of the Market ~ 25% Nodes = 1.950.426 Edges = 7.948.890 (Voice Calls) April 16 to April 30 2004 yes May 1 to May 15 2004 no May 16 to May 31 2004 yes June 1 to June 15 2004 no June 16 to June 30 2004 yes July 1 to July 15 2004 no July 16 to July 31 2004 yes August 1 to August 15 2004 yes August 16 to August 31 2004 no September 1 to September 15 2004 no September 16 to September 30 2004 yes October 1 to October 15 2004 yes October 16 to October 31 2004 no November 1 to November 15 2004 no November 16 to November 30 2004 no December 1 to December 15 2004 no December 16 to December 31 2004 no January 1 to January 15 2005 yes January 16 to January 31 2005 no February 1 to February 15 2005 no February 16 to February 28 2005 yes March 1 to March 15 2005 no March 15 to March 31 2005 yes Mobile Phone Network

13 Persistence Perseverance

14 Core-Periphery StructurePower-Law Decay

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16 P ij, i and k

17 P ij, i and C

18 P ij and

19 P ij, i, Gender and Age

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21 Gender And Age F M F M 1-M/F

22 = 0.0598 C – 0.0122 k + 0.3626 r + 0.0015 Age +0.0009 Gender +0.2506 Linear Regression Multivariate Analysis (Node Level) Correlations and Partial Correlations

23 P = 0.09 C + 0.002 k + 0.15 r – 0.03 Gender -0.002 Age + 0.35 R + 0.56TO +0.16 Linear Regression Multivariate Analysis (Tie Level) Correlations and Partial Correlations

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26 ConservedNot Conserved ConservedAB Not Conserved CD Reality Test Prediction Accuracy = A/(A+B) Sensitivity=A/(A+C)

27 Conclusions Quantitative Sociology can be performed using mobile phone billing data. As an example we studied the persistence of ties and showed that is strongly coupled to the topology of the network. This coupling is strong enough to make relatively accurate predictions about the existence of ties in the future.

28 The Product Space and its Consequences for Economic Growth Cesar A. Hidalgo R. 1 Bailey Klinger 2, A.-L. Barabasi 1, R. Haussman 2 1CCNR, Dept of Physics, University of Notre Dame 2CID, Kennedy School of Government, Harvard University

29 Area of countries proportional to ppp (GDP per Capita). Source: worldmapper.org

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31 Share of the i th product on the basket of country c at time t Share of the i th product on the basket of the world at time t ij =P(RCA i |RCA j ) ij = min{ P(RCA i |RCA j ),P(RCA j |RCA i ) } B. Balassa, The Review of Economics and Statistics 68, 315 (1986).

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34 Feenstras Trade Flows (1) (1) Feenstra, R. R. Lipsey, H. Deng, A. Ma and H. Mo. 2005. World Trade Flows: 1962-2000 NBER working paper 11040. National Bureau of Economic Research, Cambridge MA. sitc-4 import and export data.

35 Threshold = 0.55 Number of Links = 1525

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37 MALAYSIA

38 Malaysia 1975

39 Malaysia 1980

40 Malaysia 1985

41 Malaysia 1990

42 Malaysia 1995

43 Malaysia 2000

44 Density j = Fraction of the product space that seems to be developed from the j th product perspective Discovery Factor H j = Increase in density between transition product and undeveloped products.

45 Discovery Factor Density

46 P(transition | closest developed product is at proximity )

47 Denotes where region has RCA KEY

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49 Conclusion We showed: Product space is heterogeneous Constrains the development of RCA Rich and poor countries are located in distinct places of it Development Strategies should be different for rich and poor countries The structure of the space prevents economical convergence

50 Acknowledgments A.-L. Barabasi B. Klinger R. Hausmann C. Rodriguez-Sickert Kellogg Institute


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