Multi-value opinion sharing based on information source influence in agent-based network. (June 2020) - Kitajima, Eiki; Murata, Akihiro; Takadama, Keiki
Abstract: This paper proposes the information sharing algorithm for preventing propagation of wrong information in the agent-based network such as SNS, and aims at investigating the effectiveness of the proposed algorithm through the complex network such as a small world network. Towards practical applications, this paper extends the conventional opinion sharing model (OSM) to cope with the multi-value opinion from the binary opinion, and proposes the new algorithm for preventing propagation of wrong information to cope with the multi-value opinion. The intensive simulations of three types of the complex network have revealed that the accuracy of the correct opinion of agents in the proposed algorithm (called Self-information Weight Tuning (SWT)) reaches around 80% which is not affected by the number of opinion states in the multi-value opinions, while that of the conventional algorithm (called Autonomous Adaptive Tuning (AAT)) is lower than the proposed algorithm and decreases as the number of opinion states increases.