Abstract
Inspired by rapid growth and notable developments of Complex Networks Sciences, whose indispensable pillars are statistical mechanics, probability theory, and graph theory, researchers have in recent years found out that there are many interesting properties of real networks such as the Internet, social networks, a number of biological networks, the electric power grid, and so on. The purpose of this paper is to analyze log data recorded on a bulletin board system used in e-Learning faculty courses and to investigate, based on complex networks sciences, characteristic properties of communication networks in e-Learning environments. In this paper, we clarify the following matters: 1) the Small-World property (in the sense of Watts and Strogatz) is observed in most of communication networks. 2) The rich-club phenomenon is observed in some networks. 3) Communication networks whose nodes represent participants in e-Learning courses are disassortative, which means those communication networks are somewhat similar to nonhuman networks, artificial networks, or biological networks, not to social networks. In addition to those empirical evidences, we present some hypotheses concerned with communication networks structure in e-Learning environments.
