socialinms
Socialinms is a multidisciplinary framework used to study and optimize how information, norms, and behaviors spread through social networks. The term encompasses theoretical models of diffusion, practical methods for forecasting reach and impact, and design principles for influencing information flows in both online and offline contexts. While not tied to a single discipline, socialinms draws on network science, sociology, computer science, and behavioral science to analyze interactions among individuals, groups, and institutions.
The concept began appearing in academic writing in the late 2010s and early 2020s as researchers sought
Core components include networks, diffusion processes (such as independent cascade and SIR-inspired models), influence metrics, and
Applications span marketing, public health campaigns, emergency communication, and platform design. Practitioners aim to maximize beneficial
Critiques focus on privacy, manipulation risk, algorithmic bias, and the reliability of diffusion models in complex
See also: social networks, information diffusion, influence maximization, computational social science, network science, diffusion of innovations.