2019 AAAI AAAI 2019

Consensus in Opinion Formation Processes in Fully Evolving Environments

Abstract

Abstract Friedkin and Johnsen (1990) modeled opinion formation in social networks as a dynamic process which evolves in rounds: at each round each agent updates her expressed opinion to a weighted average of her innate belief and the opinions expressed in the previous round by her social neighbors. The stubbornness level of an agent represents the tendency of the agent to express an opinion close to her innate belief. Motivated by the observation that innate beliefs, stubbornness levels and even social relations can co-evolve together with the expressed opinions, we present a new model of opinion formation where the dynamics runs in a co-evolving environment. We assume that agentsโ€™ stubbornness and social relations can vary arbitrarily, while their innate beliefs slowly change as a function of the opinions they expressed in the past. We prove that, in our model, the opinion formation dynamics converges to a consensus if reasonable conditions on the structure of the social relationships and on how the personal beliefs can change are satisfied. Moreover, we discuss how this result applies in several simpler (but realistic) settings.

๐Ÿš€ Conference Pioneer โ€” AAAI 2019
๐ŸŒ‰ Interdisciplinary Bridge โ€” Artificial Intelligence and Machine Learning
๐Ÿงญ Keyword Pioneer โ€” co-evolving environment
๐Ÿ Cross-Pollinator โ€” Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy