Pawel Sobkowicz (2009)
Modelling Opinion Formation with Physics Tools: Call for Closer Link with Reality
Journal of Artificial Societies and Social Simulation
vol. 12, no. 1 11
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Received: 22-Nov-2008 Accepted: 09-Jan-2009 Published: 31-Jan-2009
Models based on single parameter have the advantage of being simple to analyse, but reproducing complex agent behaviours (when to change one's own opinion, when to refuse, how strong is the influence etc.) via a single number is rather difficult and range of options is limited.
|Table 1: Selected examples of opinion modelling works|
|Reference||Main topic||Topology||Opinion model||Agent characteristics||Link characteristics||Special features||Comparison with real data|
|Behera 2003||comparison of Sznajd and Voter models||1D||Sznajd model, Voter model||opinion (discrete)||NN, NNN, uniform strength||influence of general bias; synchronous vs. asynchronous update||none|
|Bernardes 2001||scaling of the cluster growth||2D||Sznajd model||opinion (discrete)||uniform||modified Sznajd model used to compare with empirical data; analysis applied in transient regime||yes, Brazilian elections|
|Bernardes 2002||explanation of election results and the Sznajd model on Barabasi network||3D cubic; scale free||Sznajd model||opinion (discrete)||uniform||comparing tempo of equilibrium in 3D and network topologies||yes, Brazilian elections|
|Caruso 2005||Multidimensional analysis of contexts for decisions with local agent interactions but also with effects of global factors||global connectivity||bipolar, with number of agents of fixed opinion (RC,LC) and undecided (CG)||payoff based on multidimensional context vector||global, with strengths of interaction dependent on type of agent||some agents form coalitions that do not change their opinion; general bias influence||yes, Italian and German elections|
|Conradt 2003||decision making in animals||global connectivity||binary||based on costs of synchronization of actions, also with incomplete information||global, uniform strength||contrast between `despotic' and `democratic' groups||yes, many animal groups, some references to human societies|
|Conradt 2005||review of consensus decision making in animals||many models mentioned in a review||many examples of animal behaviour|
|Deffuant 2000||presentation of consensus model with continuous opinion spectrum||global connectivity; 2D square||continuous, adjusted if opinions are closer than certain threshold||opinion, threshold for agreement||uniform strength; global connectivity or NN compared||discussion of multidimensional opinions (vector)||none|
|Deffuant 2002||consensus model with analysis of uncertainty||global||continuous, adjusted if opinions are closer than certain threshold||opinion, threshold for agreement, uncertainty||uniform strength||analysis of extreme opinions survival||none|
|Deffuant 2004||modelling opinion shift to extreme values||global||continuous, adjusted if opinions are closer than certain threshold||opinion, threshold for agreement, uncertainty||uniform strength||special agents (extremists) with opinions located at edges of the spectrum and low uncertainty are used||some reference to psychological data, no comparison|
|Dyer 2008||consensus in human crowds||no simulation model introduced||experiments on crowd behaviour|
|Elgazzar 2002||opinion formation on small-world network||small world||Sznajd model||opinion||NN and shortcuts, uniform strength||none|
|Fortunato 2004b||network universality of confidence parameter dependence||global, 2D lattice, random network, scale free network||Deffuant model, continuous||opinion, threshold for agreement||uniform||comparison of network topologies||none|
|Fortunato 2004a||combination of Sznajd and Deffuant models||2D contrasted with scale-free||modified Sznajd model||opinions, continuous||NN||weak and strong versions of opinion change are discusses||none|
|Fortunato 2005||comparison of Krause-Hegselmann, Sznajd and Deffuant models||scale free||various versions of characteristics and dynamics, corresponding to the models being compared||reactions to extreme events: external modification of single agent's opinion and subsequent dynamics||none|
|Fortunato 2007||simple `word-of-mouth' influence model used to explain election results universality||hierarchical network||unidirectional influence||candidate preference||hierarchical, unidirectional||discovery of universal features in actual election results and simple fit with `word-of-mouth' model||yes, many examples of electoral results|
|Galam 1997||achieving consensus through minimization of individual conflicts||Ising-like model; agents interact with a fixed fraction of all agents||statistical analytic considerations, no simulation; agents characterised by opinion, discrete; social pressure; internal preference||none|
|Gil 2006||opinion formation on evolving networks||initially global; as results of interactions links are cut, topology changes||opinions adjusted with probability p1, links cut with probability p2||opinion (binary)||uniform||formation of separated clusters||none|
|Hegelsmann 2002||introduction of Krause-Hegelsmann model,||global||Krause-Hegelsmann||opinion, time dependent influence matrix, susceptibility||weighted interactions with other agents||none|
|Holyst 2001||social impact of strong leaders||2D||Nowak-Latane model, with strong leaders||opinion, strength of influence, external influence, social `temperature'||weighted interactions with other agents, strength decreasing with physical distance||comparison between simulations and analytical `mean-field' approximations||none|
|Kacperski 1999||social impact of strong leaders||2D||Nowak-Latane model, with strong leaders||opinion, strength of influence, external influence, social `temperature'||weighted interactions with other agents, strength decreasing with physical distance||study of effects of flips of leader's opinions||none|
|Kacperski 2000||phase transitions of global opinions for groups with leaders||global||Nowak-Latane model, with strong leaders||opinion, strength of influence, external influence, social `temperature'||weighted interactions with other agents, strength determined by arbitrary `adjacency matrix'||presence of universal `phase transitions'||none|
|Lewenstein 1992||mean field theory of social impact||comparison of global interactions, sparse network, hierarchical network, 2D lattice||modified Nowak-Latane model||opinion (binary); persuasiveness; supportiveness||interaction strength weighted by `social distance'||comparison of various geometries; analysis of effect of noise||none|
|Lorenz 2007||survey of results under Krause-Hegelsmann and Deffuant models||global, although discussion of social network dependence is included||Krause-Hegelsmann and Deffuant||opinion (continuous, multidimensional)||uniform for defiant model, weights in the Krause-wheelsman model||comparison between agent based models and density models (which can be interpreted as limit case for infinitely many agents)||none|
|Nowak 1990||simulations for the social impact theory of Latane||2D||Nowak-Latane model||opinion (binary); persuasiveness; supportiveness||interaction strength weighted by `social distance'||some remarks on qualitative social opinion phenomena, no direct comparison with simulations|
|Nowak 1996||general introduction into social modelling; dynamic social impact||2D, some discussion on 1D case||Nowak-Latane model||opinion (binary); persuasiveness; supportiveness; self-supportiveness||variable strength of interaction, decreasing with distance||none|
|Pluchino 2005||Opinion Changing Rate model introduction||global||OCR model, stressing dynamic aspects over equilibrium||opinion (continuous, unbounded); natural opinion rate change;||variable strength of interaction, depending on opinion difference||focus on differences in tendencies to change opinions||none|
|Roehner 2005||supplementing computer opinion models with real world data||presentation of `experimental data' with some discussion of the ways of information spread through formal mass media channels as well as through informal channels (rumours, hearsay, gossip) and some macro-constraints||data on consensus formation in various countries for using cell phones while driving|
|Sabatelli 2003a||average opinion dependence in Sznajd model with noise||2D||Sznajd model with noise||opinion (binary)||uniform, NN||none|
|Sabatelli 2003b||role of update mechanism (synchronous vs. async) and memory in Sznajd model||2D||modified Sznajd model||opinion (binary)||uniform, NN||synchronous updating role discusses||none|
|Schulze 2004||results for Sznajd model with global and local interactions||2D||modified Sznajd model||opinion (discrete, with Q available options)||uniform, global for comparison of opinions, the local for conversions||Additional analysis of advertising bias for one of opinions||none|
|Schweitzer 2000||modelling collective opinion formation by means of active Brownian particles||2D, with moving agents||Nowak-Latane model||opinion (binary); social temperature; strength of influence; self-support; global bias||interaction strength given by social distance||agents are not fixed at locations, they move within the 2D geometry, to minimize the pressure on their opinion||none|
|Slanina 2003||analytical results for the Sznajd model of opinion formation||network with local and global interactions||Sznajd model||opinion (discrete, with Q available options)||uniform||analytical results for certain simplifications||none|
|Sobkowicz 2003b||comparison of results for Nowak-Latane model in various geometries and with inclusion of strong leaders||comparison of 2D, random network, scale-free network, hierarchical network||modified Kacperski-Holyst model||opinion (binary); strength; leader strength; external bias||interaction strength given by social distance||dependence of behaviours on position of leader in scale free networks||none|
|Sobkowicz 2003a||effects of leader's strategy on opinion formation||comparison of, scale-free network and short range network||modified Kacperski-Holyst model with introduction of costs of convincing other agents||opinion (binary); strength; leader strength; external bias, costs and available resources, strategy||interaction strength given by social distance and individual strategies in assigning weights to links||strategies define how each agent uses finite resources to convert others to his opinion, leaders have finite resources||none|
|Sousa 2004b||consensus formation on a triad scale-free network||special case of scale free network||modification of Sznajd model||opinion (binary and discrete spectrum)||uniform||discussion of opinion changes when conviction comes from uniform opinion of 1, 2, 3 neighbours or 3 neighbours forming a triangle||none|
|Sousa 2004a||bounded confidence model on a still growing scale-free network||scale free network||Deffuant model, continuous||opinion (continuous)||uniform||network grows at the same time as the opinions are adjusted, but no special effects were discovered||none|
|Stauffer 2001||review of Sznajd model||2D||Sznajd model||opinion (binary)||uniform||generalization to many possible states is used to explain the distribution of votes among candidates in Brazilian local elections|
|Stauffer 2002||persistence of opinion in the Sznajd consensus model||D-dimensional geometric network; D=1,2,3,4||Sznajd model||opinion (binary)||uniform||study of the number of agents that did not change their opinion||none|
|Stauffer 2003||Simulation of Consensus Model of Deffuant et al on a Barabasi-Albert Network||scale free network||Deffuant model||opinion (continuous);||uniform||behaviour of scale free network found to be similar to random one||none|
|Stauffer 2004||scaling law for defiant model on scale free network||scale free network||discretized Deffuant model||opinion (Q discrete opinions);||uniform||multi-layer model representing various age levels; advertising effects||none|
|Sznajd 2000||introduction of Sznajd model||1D chain||Sznajd model||opinion (binary)||uniform||none|
|Tessone 2004||neighbourhood models of minority opinion spreading||1D, 2D||Galam model, global and near neighbourhood interactions||opinion (binary)||uniform within local cells||effects of synchronous and asynchronous updates discussed||none|
|Weisbuch 2002||comparison of simulation results for continuous and binary opinions and for local and global interactions||global; 2D local interactions||modified Deffuant model;||opinion (multidimensional, continuous, bounded)||uniform||none|
|Weisbuch 2004||discussion of inuence of possible social networks topologies on the dynamics of Deffuant model||scale free network||Deffuant model||opinion (continuous)||uniform||none|
|Weisbuch 2005||discussion of the role or extremists in Deffuant model||global; 2D local interactions; scale free||Deffuant model||opinion (continuous)||uniform||none|
|Wu 2004||dynamical theory of opinion formation in social network||random graph||forced change of opinion on disagreement||opinion (binary)||uniform||simple analytical treatment and simulations; discussion of effects of some agents with fixed opinions||none|
ANDRESKI S (1972) Social Sciences as Sorcery. André Deutsch.
BARABSI A L, Ravasza E and Vicsek T (2001) Deterministic Scale-Free Networks. Physica A, 64:559,.
BEHERA L and Schweitzer F (2003) On Spatial Consensus Formation: Is the Sznajd Model Different from a Voter Model? International Journal of Modern Physics C, 14 (10):1331-1354.
BERNARDES A T, Costa U M S, Araujo A D and Stauffer D (2001) Damage Spreading, Coarsening Dynamics and Distribution of Political Votes in Sznajd Model on Square Lattice. International Journal of Modern Physics C, 12 (2):159-168,.
BERNARDES A T, Stauffer D and Kertész J (2002) Election results and the Sznajd model on Barabasi network. The European Physical Journal B-Condensed Matter and Complex Systems, 25(1):123-127.
CARUSO F and Castorina P (2005) Opinion dynamics and decision of vote in bipolar political systems, URL http://arxiv.org/pdf/physics/0503199.
CASTELLANO C, Fortunato S and Loreto V (2007) Statistical physics of social dynamics, URL http://arxiv.org/pdf/0710.3256. Accepted by Reviews of Modern Physics.
CHIALVO D R (2004) Critical brain networks. Physica A Statistical Mechanics and its Applications, 340:756-765.
CHIALVO D R and Bak P (1999) Learning from mistakes. Neuroscience, 90(4):1137-1148.
CONRADT L and Roper T J (2003) Group decision-making in animals. Nature, 421(6919):155-8.
CONRADT L and Roper T J (2005) Consensus decision making in animals. Trends in Ecology & Evolution, 20(8): 449-456.
DEFFUANT G, Amblard F and Weisbuch G (2004) Modelling Group Opinion Shift to Extreme: the Smooth Bounded Confidence Model, URL http://arxiv.org/pdf/cond-mat/0410199.
DEFFUANT G, Amblard F, Weisbuch G and Faure T (2002) How can extremism prevail? A study based on the relative agreement interaction model. Journal of Artificial Societies and Social Simulation, 5(4):1 URL http://jasss.soc.surrey.ac.uk/5/4/1.html.
DEFFUANT G, Neau D, Amblard F and Weisbuch G (2000) Mixing beliefs among interacting agents. Advances in Complex Systems, 3:87-98.
DOROGOVTSEV S N and Mendes J F F (2003) Evolution of Networks From Biological Nets to the Internet and WWW. Oxford University Press, 2003.
DOROGOVTSEV S N and Mendes J F F (2002) Evolution of networks. Advances in Physics, 51:1079-1087.
DYER J R, Ioannou C C, Morrell L J, Croft D P, Couzin I D, Waters D A and Krause J (2008) Consensus decision making in human crowds. Animal Behaviour, 75(2):461-470.
ELGAZZAR A S (2002) Applications of Small-World Networks to some Socio-economic Systems, URL http://arxiv.org/pdf/cond-mat/0212071.
EPSTEIN J M (2008) Why Model? Journal of Artificial Societies and Social Simulation, 11(4):12 http://jasss.soc.surrey.ac.uk/11/4/12.html.
FORTUNATO S and Castellano C (2007) Scaling and Universality in Proportional Elections. Physical Review Letters, 99(13):138701.
FORTUNATO S (2004a) The Sznajd Consensus Model with Continuous Opinions, URL http://arxiv.org/abs/cond-mat/040735.
FORTUNATO S (2004b) Universality of the Threshold for Complete Consensus or the Opinion Dynamics of Deffuant et al., URL http://arxiv.org/pdf/cond-mat/0406054v1.
FORTUNATO S and Stauffer D (2005) Computer Simulations of Opinions URL http://arxiv.org/abs/cond-mat/0501730.
GALAM S (1997) Rational Group Decision Making. A random field Ising model at T=0. Physica A, 238:66-80.
GIL S and Zanette D H (2006) Coevolution of agents and networks: Opinion spreading and community disconnection. Physics Letters A, 356(2):89-94.
HEGSELMANN R and Krause U (2002) Opinion dynamics and bounded confidence models, analysis, and simulation. Journal of Artificial Societies and Social Simulation (JASSS) 5(3)2 http://jasss.soc.surrey.ac.uk/5/3/2.html.
HOLYST J A, Kacperski K and Schweitzer F (2001) Social impact models of opinion dynamics. Annual Review of Comput. Phys., 20:531-535.
JOHN E R (2001) A field theory of consciousness. Conscious Cogn, 10(2):184-213.
KACPERSKI K and Holyst J A (1999) Opinion formation model with strong leader and external impact: a mean field approach. Physica A, 269:511-526.
KACPERSKI K and Holyst J A (2000) Phase transitions as a persistent feature of groups with leaders in models of opinion formation. Physica A, 287:631-643.
LEWENSTEIN M, Nowak A, and Latané B. (1992) Statistical mechanics of social impact. Phys. Rev. A, 45:763-776.
LORENZ J (2007) Continuous Opinion Dynamics Under Bounded Confidence: A Survey. International Journal of Modern Physics C, 18 (12):1819.
MILGRAM S (1967) The Small World Problem. Psychology Today, 2:62-67, 1967.
MOSS S and Edmonds B (2005) Towards Good Social Science. Journal of Artificial Societies and Social Simulation, 8(4):13 http://jasss.soc.surrey.ac.uk/8/4/13.html.
NEWMAN M E J (2000) Models of the small world. J. Stat. Phys., 101:819-841.
NEWMAN M E J and Park J (2003) Why social networks are different from other types of networks. Physical Review E, 68(3):36122.
NOWAK A and Lewenstein M (1996) Modeling Social Change with Cellular Automata. In Rainer Hegselmann, Ulrich Mueller, and Klaus G. Troitzsch, editors, Modelling and Simulation in the Social Sciences From A Philosophy of Science Point of View, pages 249-285. Kluver, Dordrecht.
NOWAK A, Szamrej J and Latané B (1990) From Private Attitude to Public Opinion: A Dynamic Theory of Social Impact. Psychological Review, 97(3):362-376.
PARKINSON C N (1958) Parkinson's Law: The Pursuit of Progress. John Murray.
PLUCHINO A, Latora V, and Rapisarda A (2005) Changing Opinions in a Changing World: a New Perspective in Sociophysics, Int. J. Mod. Phys. C 1694):515--531.
ROEHNER B M (2005) Consensus formation: The case of using cell phones while driving, URL http://arxiv.org/abs/physics/0502046.
SABATELLI L and Richmond P (2003a) Non-monotonic spontaneous magnetization in a Sznajd-like Consensus Model. URL http://xxx.lanl.gov/pdf/cond-mat/0309375.
SABATELLI L and Richmond P (2003b) Phase transitions, memory and frustration in a Sznajd-like model with synchronous updating. URL http://xxx.lanl.gov/pdf/cond-mat/0305015.
SCHELLING T S (1971) Dynamic Models of Segregation. Journal of Mathematical Sociology, 1:143-186.
SCHULZE C (2004) Sznajd opinion dynamics with global and local neighbourhood, URL http://arxiv.org/pdf/cond-mat/0402397.
SCHWEITZER F and Holyst J A (2000) . Modelling collective opinion formation by means of active Brownian particles. European Physical Journal B, 15:723-732.
SIMKIN M V and Roychowdhury V P (2003) Read before you cite. Complex Systems, 14:269-274.
SIMKIN M V and Roychowdhury V P (2005a) Copied Citations Create Renowned papers? Annals of Improbable Research,, January-February 2005, pages 24-27 .
SIMKIN M V and Roychowdhury V P (2005b) Stochastic modeling of citation slips. Scientometrics, 62(3):367-384.
SIMKIN M V and Roychowdhury V P (2006) An introduction to the theory of citing. Significance, 3:179.
SLANINA F and Lavicka H (2003) Analytical results for the Sznajd model of opinion formation. European Physical Journal B - Condensed Matter, 35(2):279-288.
SOBKOWICZ P (2003a) Effect of leader's strategy on opinion formation in networked societies. URL http://arxiv.org/pdf/cond-mat/0311566.
SOBKOWICZ P (2003b) Opinion formation in networked societies with strong leaders, URL http://arxiv.org/pdf/cond-mat/0311521.
SOUSA A O (2004a) Bounded confidence model on a still growing scale-free network, URL http://arxiv.org/pdf/cond-mat/0406766.
SOUSA A O (2004b) Consensus formation on a triad scale-free network, URL http://arxiv.org/pdf/cond-mat/0406390.
SPORNS O, Tononi G and Edelman G M (2000) Connectivity and complexity: the relationship between neuroanatomy and brain dynamics. Neural Networks, 13(8-9):909-922.
STAUFFER D and de Oliveira P M C (2002) Persistence of opinion in the Sznajd consensus model: computer simulation. The European Physical Journal B-Condensed Matter, 30 (4):587-592.
STAUFFER D and Meyer-Ortmanns H (2003) Simulation of Consensus Model of Deffuant et al on a Barabasi-Albert Network, URL http://arxiv.org/pdf/arXiv:cond-mat/0308231.
STAUFFER D, Sousa A and Schulze C (2004) Discretized Opinion Dynamics of The Deffuant Model on Scale-Free Networks. Journal of Artificial Societies and Social Simulation, 7(3)7 http://jasss.soc.surrey.ac.uk/7/3/7.html.
STAUFFER D (2001) Monte Carlo simulations of Sznajd models. Journal of Artificial Societies and Social Simulation, 5(1)4 http://jasss.soc.surrey.ac.uk/5/1/4.html.
STROGATZ S H (2001) Exploring complex networks. Nature, 410:268-276.
SZNAJD-WERON K and Sznajd J (2000) Opinion Evolution in Closed Community. Int. J. Mod. Phys. C, 11:1157-1166.
TESSONE C J, Toral R, Amengual P, Wio H S and San Miguel M (2004) Neighborhood models of minority opinion spreading. The European Physical Journal B-Condensed Matter, 39 (4):535-544.
WATTS D J (1999). Small Worlds. Princeton University Press, Princeton.
WATTS D J and Strogatz S H (1998) Collective dynamics of 'small-world' networks. Nature, 393:440-442.
WEISBUCH G (2004) Bounded confidence and social networks. The European Physical Journal B-Condensed Matter and Complex Systems, 38(2):339-343.
WEISBUCH G, Deffuant G, and Amblard F (2005) Persuasion dynamics. Physica A: Statistical Mechanics and its Applications, 353:555-575.
WEISBUCH G, Deffuant G, Amblard F and Nadal J P (2002) Meet, Discuss, and Segregate! Complexity, 7(3):55-63.
WILLIAMS L E and Bargh J A (2008) Experiencing Physical Warmth Promotes Interpersonal Warmth. Science, 322(5901):606.
WU F and Huberman B A (2004) Social Structure and Opinion Formation, URL http://arxiv.org/pdf/cond-mat/0407252.
ZANETTE D H and Gil S (2006) Opinion spreading and agent segregation on evolving networks. Physica D: Nonlinear Phenomena, 224(1-2): 156-165, 2006.
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