Skip to main content
SpringerLink
Log in

A Computational Experiment to Describe Opinion Formation Using a Master Equation and Monte Carlo Simulations

  • Conference paper
Emerging Technologies and Information Systems for the Knowledge Society (WSKS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5288))

Included in the following conference series:

  • 2012 Accesses

Abstract

We propose a computer simulation model aiming to describe the interaction of students in a learning environment composed of the teacher, the students in a collaborative project and the educational material. Our aim is to investigate the change of the opinion of students when they interact with an agent with different opinion. This model can apply to all levels of education in order to explore the reconciliation or not of different opinions during the teaching and learning sequence as well as to examine the resistance of students to new challenges and concepts. The idea is based on the social impact theory and uses methods of Computational Physics, mainly the Monte Carlo techniques and the notion of master equation. Results from simulations indicate that opinion formation is established for different values of the populations when the temperature is below the critical temperature.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 149.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anderson, P.W.: Basic Notions of Condensed Matter Physics. Addison-Wesley, Reading (1997)

    Google Scholar 

  2. Barbour, I., Psycharis, S.: SU(2) and SU(3) Gauge Theories on a Lattice with Twisted Boundary Conditions. Nuclear Physics B 334, 302–308 (1990)

    Article  Google Scholar 

  3. Berliner, D.C., Calfee, R.C.: Handbook of Educational Psychology. MacMillan, New York (1996)

    Google Scholar 

  4. Binder, K.: Application of the Monte Carlo Method in Statistical Physics. Springer, Heidelberg (1987)

    Google Scholar 

  5. Bonabeau, E.G., Theraulaz, G., Deneubourg, J.L.: Phase diagram of a model of self-organizing hierachies. Physica A 217, 373 (1995)

    Google Scholar 

  6. Clelia, M., Ezequiel, V.: Theoretical Description of Teaching-Learning Processes: A Multidisciplinary Approach. Physical Review Letters 87(11) (2001)

    Google Scholar 

  7. Cohen, J.: Statistical power analysis for the behavioural sciences. Lawrence Erlbaum, Hillsdale (1988)

    Google Scholar 

  8. Coombs, S., Smith, I.: Designing a self-organized conversational learning environment. Educational Technology 38(3), 17–28 (1998)

    Google Scholar 

  9. Cowan, G.A., Pines, D., Meltzer, D.: Complexity: Metaphors, Models and Reality. Addison-Wesley, Santa Fe (1994)

    MATH  Google Scholar 

  10. Dongarra, J., Sullivan, F.: Computing in Science and Engineering 2.2,  2(1), 22–23 (2000) ISSN: 1521-9615

    Google Scholar 

  11. Epstein, J.M.: Remarks on the Foundations of Agent-Based, Generative Social Science. In: Tesfatsion, L., Judd, K. (eds.) Handbook of Computational Economics II. Elsevier, Amsterdam (2006)

    Google Scholar 

  12. Galam, S.: Fragmentation versus stability in bimodal coalitions. Physica A 230, 174–188 (1996)

    Article  Google Scholar 

  13. Galam, S.: Rational group decision making: A random field ising model at t = 0. Physica A 238, 66–80 (1997)

    Google Scholar 

  14. Gilbert, N., Doran, J.: Simulating Societies: The Computer Simulation of Social Processes. University College, London (1994)

    Google Scholar 

  15. Glance, N.S., Huberman, B.A.: The outbreak of cooperation. J. Math. Sociology 17(4), 281 (1993)

    MATH  Google Scholar 

  16. Glasersfeldt, E.: Constructivism in education. In: Husén, T.T., Postlethwaite, T.L. (eds.) The international encyclopedia of education, pp. 11–12. Pergamon, Oxford (1989)

    Google Scholar 

  17. Haag, G., Weidlich, W.: A dynamic phase transition model for spatial agglomeration processes. Journal of Regional Science 27(4), 529–569 (1987)

    Article  Google Scholar 

  18. Haag, G., Weidlich, W.: Concepts and Models of a Quantitative Sociology. The Dynamics of Interacting Populations. Springer, Berlin (1983)

    MATH  Google Scholar 

  19. Haag, G., Weidlich, W.: Interregional Migration. Springer, Berlin (1988)

    Google Scholar 

  20. Hake, R.R.: Interactive-engagement versus traditional method: A six-thousand-student survey of mechanics test data for introductory physics courses. American Journal of Physics 66(1), 64–74 (1998)

    Article  Google Scholar 

  21. Helbing, D.: A mathematical model for the behavior of pedestrians. Behavioral Science 36, 298–310 (1991)

    Article  Google Scholar 

  22. Helbing, D.: Quantitative Sociodynamics. Kluwer Academic, Dordrecht (1995)

    MATH  Google Scholar 

  23. Helbing, D.: Stochastic and Boltzmann-like models for behavioral changes and their relation to game theory. Physica A 193, 241–258 (1993)

    Article  MathSciNet  Google Scholar 

  24. Heller, J.I., Reif, F.: Prescribing effective human problem solving processes: Problem descriptions in physics. Cognition and Instruction 1(2), 177–216 (1984)

    Article  Google Scholar 

  25. Holyst, J., Krzystzof, K., Schweitzer, F.: Social Impact Models Of Opinion Dynamics. In: Stauffer, D. (ed.) Annual Reviews of Computational Physics IX, pp. 253–273. World Scientific Publishing Company, Singapore (2001)

    Google Scholar 

  26. Janssen, M., Jager, W.: An Integrated Approach to Simulating Behavioural Processes: A Case Study of the Lock-In of Consumption Patterns. JASSS - Journal of Artificial Societies and Social Simulation 2(2) (1999)

    Google Scholar 

  27. Kohring, G.A.: Ising models of social impact: the role of cumulative advantage. J. Phys. I. France 6, 301 (1998)

    Google Scholar 

  28. Latane, B.: Am. Psychologist 36, 343 (1981)

    Google Scholar 

  29. Latané, B.: Dynamic Social Impact: Robust Predictions from Simple Theory. In: Hegselmann, R., Mueller, U., Troitzsch, K. (eds.) Modeling and Simulation in the Social Sciences from a Philosophy of Science Point of View. Kluwer, Dorderecht (1996)

    Google Scholar 

  30. Latané, B.: Pressures to Uniformity and the Evolution of Cultural Norms. Modeling Dynamics Social Impact. In: Hulin, C., Ilgen, D. (eds.) Computational Modeling of Behavior in Organizations. The Third Scientific Discipline, pp. 189–215. American Psychological Association, Washington (2000)

    Google Scholar 

  31. Lewenstein, M., Nowak, A., Latane, B.: Phys. Rev. A 45, 763 (1992)

    Google Scholar 

  32. Liu, J.: Monte Carlo Techniques in Scientific Computing. Springer, New York (2001)

    Google Scholar 

  33. Lorenz, H.W.: Nonlinear Dynamical Equations and Chaotic Economy. Springer, Berlin (1993)

    Google Scholar 

  34. Mantegna, R.N., Stanley, H.E.: An Introduction to Econophysics. Cambridge University Press, Cambridge (2000)

    Google Scholar 

  35. Meadows, D.L., Behrens, W.W., Meadows, D.H., Naill, R.F., Randers, J., Zahn, E.K.: The Dynamics of Growth in a Finite World. MIT Press, Cambridge (1974)

    Google Scholar 

  36. Metropolis, N., Arianna, W., Rosenbluth, A., Teller, E.: Equation of state calculations by fast computing machines. The Journal of Chemical Physics 21(6), 1087–1092 (1953)

    Google Scholar 

  37. Oliveira, P.M., Stauffer, D., Oliveira, M.S., Zorzenon, R.M.: Monte Carlo Simulations of Sexual Reproduction. Physica, A 231, 504 (1996)

    Google Scholar 

  38. Prietula, M., Carley, K., Gasser, L.: Simulating Organizations: Computational Models of Institutions and Groups. MIT Press, Cambridge (1998)

    Google Scholar 

  39. Reif, F., Heller, J.I.: Knowledge structure and problem solving in physics. Educational psychologist 17(2), 102–127 (1982)

    Google Scholar 

  40. Stauffer, D.: Journal of Arificial Societies and Social Simulation 5 (2002)

    Google Scholar 

  41. Vallacher, R., Nowak, A.: Dynamical Systems in Social Psychology. Academic, New York (1995)

    Google Scholar 

  42. Sweller, J.: Cognitive load during problem solving: Effects on learning. Cognitive Science 12, 257–285 (1988)

    Google Scholar 

  43. Vallacher, R.R., Nowak, A.: Dynamical Systems in Social Psychology. Academic, San Diego (1994)

    Google Scholar 

  44. Weidlich, W., Haag, G.: Concepts and Models of Quantitative Sociology. Springer, Berlin (1983)

    Google Scholar 

  45. Weidlich, W.: Physics and social science - The approach of synergetics. Physics Reports 204, 1–163 (1991)

    Google Scholar 

  46. Weidlich, W.: Physics and social science | the approach of synergetics. Phys. Rep. 204 (1991)

    Google Scholar 

  47. Weidlich, W.: Sociodynamics: A Systematic Approach to Mathematical Modelling in the Social Sciences. Harwood Academic Publishers (2000)

    Google Scholar 

  48. Psycharis, S.: Is there a spontaneous symmetry breaking during the learning process? The use of Monte Carlo Simulation and the Metropolis Algorithm in order to determine the time evolution of the learning efforts. Journal Mentoras (2008) (in Greek)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of the Aegean-Department of Education and Advanced School of Pedagogy and Technology ASPETE-Athens,  

    Sarantos Psycharis

  2. School of Pedagogy and Technology ASPETE,  

    Evi Makri-Botsari & Gregorios Mouladidis

  3. University of Piraeus,  

    Fotini Paraskeva

  4. University of the Aegean,  

    Vassilis Tatsis

Authors
  1. Sarantos Psycharis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Evi Makri-Botsari
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gregorios Mouladidis
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fotini Paraskeva
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Vassilis Tatsis
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Miltiadis D. Lytras John M. Carroll Ernesto Damiani Robert D. Tennyson

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Psycharis, S., Makri-Botsari, E., Mouladidis, G., Paraskeva, F., Tatsis, V. (2008). A Computational Experiment to Describe Opinion Formation Using a Master Equation and Monte Carlo Simulations. In: Lytras, M.D., Carroll, J.M., Damiani, E., Tennyson, R.D. (eds) Emerging Technologies and Information Systems for the Knowledge Society. WSKS 2008. Lecture Notes in Computer Science(), vol 5288. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87781-3_53

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-87781-3_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87780-6

  • Online ISBN: 978-3-540-87781-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation