Data-Informed Modeling of the Formation, Persistence, and Evolution of Social Norms and Conventions

Mengbin Ye () and Lorenzo Zino ()
Additional contact information
Mengbin Ye: Curtin University, Centre for Optimisation and Decision Science
Lorenzo Zino: Politecnico di Torino, Department of Electronics and Telecommunications

A chapter in Handbook of Visual, Experimental and Computational Mathematics, 2026, pp 975-1010 from Springer

Abstract: Abstract Social norms and conventions are commonly accepted and adopted behaviors and practices within a social group that guide interactions—e.g., how to spell a word or how to greet people—and are central to a group’s culture and identity. Understanding the key mechanisms that govern the formation, persistence, and evolution of social norms and conventions in social communities is a problem of paramount importance for a broad range of real-world applications, spanning from preparedness for future emergencies to promotion of sustainable practices. In the past decades, mathematical modeling has emerged as a powerful tool to reproduce and study the complex dynamics of norm and convention change, gaining insights into their mechanisms, and ultimately deriving tools to predict their evolution. The first goal of this chapter is to introduce some of the main mathematical approaches for modeling social norms and conventions, including population models and agent-based models relying on the theories of dynamical systems, evolutionary dynamics, and game theory. The second goal of the chapter is to illustrate how quantitative observations and empirical data can be incorporated into these mathematical models in a systematic manner, establishing a data-based approach to the mathematical modeling of the formation, persistence, and evolution of social norms and conventions. Finally, current challenges and future opportunities in this growing field of research are discussed.

Keywords: Agent-based models; Cascade; Complex networks; Data science; Dynamical systems; Evolutionary dynamics; Psychology experiments; Game theory (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-032-16368-4_15

Ordering information: This item can be ordered from
http://www.springer.com/9783032163684

DOI: 10.1007/978-3-032-16368-4_15

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().