Citing this article

A standard form of citation of this article is:

Salzarulo, Laurent (2006). 'A Continuous Opinion Dynamics Model Based on the Principle of Meta-Contrast'. Journal of Artificial Societies and Social Simulation 9(1)13 <http://jasss.soc.surrey.ac.uk/9/1/13.html>.

The following can be copied and pasted into a Bibtex bibliography file, for use with the LaTeX text processor:

@article{salzarulo2006,
title = {A Continuous Opinion Dynamics Model Based on the Principle of Meta-Contrast},
author = {Salzarulo, Laurent},
journal = {Journal of Artificial Societies and Social Simulation},
ISSN = {1460-7425},
volume = {9},
number = {1},
pages = {13},
year = {2006},
URL = {http://jasss.soc.surrey.ac.uk/9/1/13.html},
keywords = {Opinion Dynamics, Self-Categorization Theory, Consensus, Polarization, Extremism},
abstract = {We propose a new continuous opinion dynamics model inspired by social psychology. It is based on a central assumption of self-categorization theory called principle of meta-contrast. We study the behaviour of the model for several network interactions and show that, in particular, consensus, polarization or extremism are possible outcomes, even without explicit introduction of extremist agents. The model is compared to other existing opinion dynamics models.},
}

The following can be copied and pasted into a text file, which can then be imported into a reference database that supports imports using the RIS format, such as Reference Manager and EndNote.


TY - JOUR
TI - A Continuous Opinion Dynamics Model Based on the Principle of Meta-Contrast
AU - Salzarulo, Laurent
Y1 - 2006/01/31
JO - Journal of Artificial Societies and Social Simulation
SN - 1460-7425
VL - 9
IS - 1
SP - 13
UR - http://jasss.soc.surrey.ac.uk/9/1/13.html
KW - Opinion Dynamics
KW - Self-Categorization Theory
KW - Consensus
KW - Polarization
KW - Extremism
N2 - We propose a new continuous opinion dynamics model inspired by social psychology. It is based on a central assumption of self-categorization theory called principle of meta-contrast. We study the behaviour of the model for several network interactions and show that, in particular, consensus, polarization or extremism are possible outcomes, even without explicit introduction of extremist agents. The model is compared to other existing opinion dynamics models.
ER -