Soil: An Agent-Based Social Simulator in Python for Modelling and Simulation of Social Networks

• Published in: Advances in Practical Applications of Cyber-Physical Multi-Agent Systems: The PAAMS Collection Vol. 10349; pp. 234 - 245
• Main Authors: Sánchez, Jesús M., Iglesias, Carlos A., Sánchez-Rada, J. Fernando
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2017; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Exponential Random Graph Model; Network Visualisation; Social Graph; Social Network; Social Network Analysis
• ISBN: 3319599291; 9783319599298
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-59930-4_19

Social networks have a great impact in our lives. While they started to improve and aid communication, nowadays they are used both in professional and personal spheres, and their popularity has made them attractive for developing a number of business models. Agent-based Social Simulation (ABSS) is one of the techniques that has been used for analysing and simulating social networks with the aim of understanding and even forecasting their dynamics. Nevertheless, most available ABSS platforms do not provide specific facilities for modelling, simulating and visualising social networks. This article aims at bridging this gap by introducing an ABSS platform specifically designed for modelling social networks. The main contributions of this paper are: (1) a review and characterisation of existing ABSS platforms; (2) the design of an ABSS platform for social network modelling and simulation; and (3) the development of a number of behaviour models for evaluating the platform for information, rumours and emotion propagation. Finally, the article is complemented by a free and open source simulator.