Modeling Social Influence in Social Networks with SOIL, a Python Agent-Based Social Simulator

• Published in: Advances in Practical Applications of Cyber-Physical Multi-Agent Systems: The PAAMS Collection Vol. 10349; pp. 337 - 341
• Main Authors: Merino, Eduardo, Sánchez, Jesús M., García, David, Sánchez-Rada, J. Fernando, Iglesias, Carlos A.
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2017; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Brand reputation; Python; Rumor propagation; Social network; SOIL; Viral marketing
• ISBN: 3319599291; 9783319599298
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-59930-4_33

The application of Agent-based Social Simulation (ABSS) for modeling social networks requires specific facilities for modeling, simulation and visualization of network structures. Moreover, ABSS can benefit from interactive shell facilities that can assist the model development process. We have addressed these problems through the development of a tool called SOIL, which provides a Python ABSS specifically designed for social networks. In this paper we present how this tool is applied to simulate viral marketing processes in a social network, and to evaluate the model with real data.