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Santo Fortunato. Phenomenology of social dynamics. Outline. Prologue Building a phenomenology: 1) elections 2) collective opinion shifts Outlook. Physics. Society!. Sociophysics. From individuals that interact locally to collective behaviour and organization. Risky business!.
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Santo Fortunato Phenomenology of social dynamics
Outline • Prologue • Building a phenomenology: 1) elections 2) collective opinion shifts • Outlook
Sociophysics From individuals that interact locally to collective behaviour and organization.
Risky business! People are not atoms: their interactions are not reproducible! Necessary condition: the size of the social groups must be big (large scale behaviour) In this way, the phenomena won’t be much affected by individual features
Interesting aspects for statistical physicists: • Large-scale regularities: scaling • Universal features • Microscopic origin of macroscopic behaviour Quantitative understanding!
Focus: opinion dynamics • Opinion dynamics models explain if and when consensus is formed or not • Shall we content ourselves with such a qualitative description? • Is it possible to validate this approach?
Building a phenomenologyof social dynamics • Elections • Collective opinion shifts Quantitative characterization of large scale social phenomena
Elections • Large scale social phenomenon • Lots of available data
Elections State elections in Brazil 1998 (Costa Filho et al., PRE, 1999) v = # votes received by a candidate Focus: distribution of v across all candidates 1/v behavior
Elections in Brazil 2002 (Costa Filho et al., Physica A 2003) 1/v decay reproducible over the years
Indian elections (González et al. IJMPC, 2004) • 1/v decay occurs in different countries • Is it universal?
Problem: is it correct to put together candidates of different parties? Support for different parties wildly fluctuates!
Position of parties is more or less known on relevant issues • Party is selected depending on the issues • Candidate to be voted is chosen depending on the existence of some form of direct/indirect contact with the voter → model!
N = total votes for party Q = number of party candidates A new analysis (S.F. & C. Castellano, physics/0612140) Proportional elections with open lists Examples: Italy (1946-1992), Poland, Finland Distribution of votes for candidates within a party P(v,Q,N)
Scaling I Only two independent variables! P(v,Q,N)=P*(v,N/Q)= P*(v,v0)
Scaling II Only one independent variable! P(v,Q,N)=P*(v,N/Q)= F(vQ/N)!
Conclusion of election analysis Same behaviour in different countries and years: the dynamics must be elementary!
Collective opinion shifts Studied by Michard and Bouchaud (2004) Principle: imitation + social pressure lead to collective effects with rapid variations Examples: crowd panic, financial crashes, economic crisis, boom of new products, etc.
A model Binary choices: Si=+1,-1 • each agent i has a personal opinion Φi, real in ]-∞,+∞[, distribution R(Φ) • public information: a field F(t) in ]-∞,+∞[ acting on all agents • social pressure: agent i is affected by “neighboring” agents, coupling Jij Three ingredients:
Field F varies from -∞ to +∞, which O(F)? Random Field Ising Model at T=0 J. Sethna et al., Nature 410, 242 (2001)
For J larger than a critical Jc, O(F) has a discontinuity at some Fc(J) (opinion swings)
For J <~ Jc G(x) is universal, i.e. independent of R(Φ)
h w Characteristic relation between height h and width w of the curve:
O t Assumption: collective opinion shifts occur near criticality Expectation/hope: recovering the peak of G(x) from real data!
Birth rates in Europe Drop in most European countries in the period 1950-2000
Cell phones in Europe Total number of cell phones in use in various European countries in the last decade
Outlook • The distribution of the number of votes received by candidates of the same party in proportional elections is universal! • Collective opinion shifts are characterized by a universal pattern of variation for the speed of change • Search for other regularities in data is necessary to create a “physical” phenomenology in social dynamics