Extending the Naming Game in Social Networks to Multiple Hearers Per Speaker

Social conventions govern numerous behaviors of humans engaging in day-to-day activities from how they greet to languages they speak. The classical Naming Game algorithm has been defined with inherently sequential semantics where agents engage in pairwise interactions and reach global consensus in the absence of any outside coordinating authority. In this paper, we extend the classic Naming Game to multiple hearers per speaker in each conversation even while allowing simultaneous “speaking” and “hearing”. We simulate the impact on the number of conversations for convergence by varying the number of hearers and investigate the impact of multiple network types and agent population sizes on the global convergence. The results show that our extended model combining simultaneous conversations and multiple hearers per speaker per conversation makes the words diffuse at a much faster rate and leads to significantly faster consensus formation.