Durkheim's Theory Of Opinion Dynamics

ABSTRACT Human beings are social animals in this animal diversity and its position lies on the top in terms of intelligence and decision making. So, being human it’s our utter responsibility to provide an optimization algorithm that is inspired by creative human thinking process.

Human interactions results in various kinds of opinion in a society. In the field of social physical world, study about dynamics of opinions is a key area. The opinion dynamics is the field related to decision making or so called opinion consensus. Opinion formation comes with collective intelligence generated from interaction and also with individual to individual. Here, we demonstrate that how human opinion dynamics can be used for solving optimization problems.

He argued on the parallelism between individualism and agglomeration in the society. He argued that integrating forces motivate individuals to conform and adopt values/norms similar to others, at the same time, disintegrative forces that encourage individualism threaten the social integration. Recently, Mas et al. 12 simulated a model of social influence based on Durkheim's theory of social integration, that besides anomie and monoculture shows a pluralistic phase characterized by opinion clustering, i.e. it combines the integrative tendencies of social influence

Firstly, Initialize opinions for every dimension d by random assignment of values from (Xmin, Xmax) to society.opinions;

2. iteration = 0;

3. WHILE (iteration < max_iteration && error > = min_error) DO

4. society.fitness = EvaluateFitnessFunction(society.opinions);

5. society.ranking = calculateRank(society.fitness); // It ranks the individuals based on society fitnessiter = iter + 1;

6. FOR each individual i and each dimension d DO

7. Calculate wij of neighbours j of individual i with respect to dimension d.

8. Update opinion of individual i as defined above. END (FOR)

END (WHILE)

Reference 1 2–8

Conclusion

Human opinion dynamics is used to resolve complex optimization problems. It leads us to an optimal solution which is based on creative thinking and dependant on knowledge gain through interaction.

If we look at it from social physics point of view these opinion dynamics models are very naive and limited in nature but we feel that the present research will provide us a path in developing the novel methods and tools to realize the real world problem solving by human beings in a social