Investment-Driven Social Influence: A Statistical Physics Approach to Advertising Response

AbstractThis paper explores social influence in consumer responses to advertising through investment-mediated conversational dynamics. We implement conversational engagement via advertising expenditure patterns, recognizing that marketing spend directly translates into conversational volume and reach across multi-channel ecosystems. Our approach integrates social psychology frameworks with statistical physics analogies as epistemic scaffolding following Ruse’s änalogy as heuristic” idea. The model introduces three parameters—Marketing Sensitivity, Response Sensitivity, and Behavioral Sensitivity—quantifying emergent properties of investment-driven influence networks. Validation against three real-world datasets shows competitive performance compared to conventional approaches of modeling the consumer response curve like Michaelis-Menten and Hill equations, with context-dependent advantages in network-driven scenarios. These findings illustrate how advertising ecosystems operate as complex adaptive systems (CAS) where influence propagates through investment-amplified conversational networks.