Distortion in Social Networks: Comparison of Various Types of Networks

Following the information revolution, enormous numbers of companies and individuals transfer by messages via social networks and/or in companies' communication networks. These messages, however, are subject to modifications as they spread through the network. This study calculates the distortion of a message as it spreads in a social network, and compares a global measurement of the distortion in random, scale free and small world networks. We create a mathematical model to describe the distortion process, and we tested it using a simulation of different types of networks. We show that scale-free networks are the least sensitive to distortion of information compared to random or small world networks.