CIUCEU: Multi-Agent–Based Simulation of University Email Communities

Introduction

Networks are pervasive in our lives. They are everywhere, from the Internet, to biology, to social relations or economics (M. Newman, Barabasi, & Watts, 2006). The notion of a connected world is one that we assume is prevalent as a foundation. The connectedness of daily things prevails, even when one segments it into sub-networks. Everything seems related, in some sense, to everything else.

In communication, the notion of networks is always present. Formal and informal relations arise from the interplay of actors during communication processes. Traditionally, networks have been categorized into four types, or classes: lattice networks, that are very regular and rigid, where a certain pattern is repeated ad infinitum; random networks, in which every connection is established according to some probability p_c; small-world networks that are somewhat in between random networks and lattice networks, and have high transitivity and short average path lengths; and finally scale-free networks that have the same type of structure at different levels, with a characteristic hub and spoke structure, where every connection is made according to the degree of existing connections. In this scenario, informal communication networks seem to be formed according to other types of rules, as they can’t truly be mapped into one of those four types of networks. These non-trivial networks, arise from the “social” aspect of these kinds of networks and several authors have discussed the problems of those four types of networks in failing to explain social networks. The problems that informal social communication networks present make them well-suited to be tested under new models of network formation and actor interplay. Multi-agent-based simulation is a popular field where these ideas can be tested and where ideas can be benchmarked.

In the next sections, we discuss the mechanisms presently available for community detection, mainly those developed with networks in mind, and we discuss some application of these algorithms to informal email communication systems through a case study. Also, we present a multi-agent model developed for exploring the influence of using real data in simulation and to test the idea of a “social neighborhood” in the formation of informal assortative communication networks.