Real emotions for simulated social networks

Abstract

In this study we analyzed how to consider real emotions in complex networks. The main idea is to understand subjects' behaviors in specific situations, such as social network sites navigation, to use these information in modeling complex phenomena. We suggest the use of agent-based models, since this is a flexible and powerful tool in complex systems modeling; moreover such models are able to include behavioral cues for heterogeneous agents: this is an important property above all considering the study of networked agents representing subjects and relationships. To have a precise idea about the subjects' behavior during social network site navigation, we used wearable biosensors in an experiment with 28 subjects to assess cardiorespiratory aspects (using a belt respiration sensor and a electrocardiogram), and facial cues (using two facial electromyography sensors). Subjects showed an optimal experience during navigation and this information gave us the chance to discuss an example of information diffusion using both a mathematical model and an agent-based model.