Análisis del efecto de la estructura topológica de las redes sociales complejas sobre la génesis de capital social a través de simulaciones informática basada en agentes

Abstract

My research work is made up of two parts. The first part is a series of original theoretical essays, and the second part is a set of simulation experiments. In the first part I have tried to answer three important questions: a) What is social simulation and why should sociologists use social simulation to research social phenomena? Since my methodological answer to this key question depends on my epistemological approach and my own epistemological position in turn depends on my point of ontological view, my reply depend on how I conceive ontologically society and sociology. b) What is social Capital? For this question, I have developed a series of original arguments in favour of the structural and objective vision of social capital (Coleman, Bourdieu) and I have also criticized the culturalist and subjective view of social capital (Putnam, Fukuyama) from evolutionary game theory. c) What is the complex structure of social networks? I have written a critical review about this subject from the works of Barabási, Coleman, Granovetter, Milgram and Watts. For the second part of my work, I wrote a computer programme (in C++ Builder5 and NetLogo) to perform some simulation experiments. The most interesting result from these experiments is that social capital depends on the Gini index of the distribution of links between nodes in the network, in other words, social capital ultimately depends on social inequality. Such experiments show us the existence of an optimum Gini index in the genesis of social capital. That is to say, for Gini indices which are superior or inferior to that optimum, the speed of information transmission and the generation of confidence is always less. Networks which have that optimum Gini index have more social capital and thus allow democracy to work better and the economy to develop more adequately than networks that do not have that optimum Gini index.