Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
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Crowd simulation is to produce collective behaviors through simulating the movement process of a number of agents. Information diffusion is to investigate how information propagates among people, especially on social network. This work considers both the spatial and social perspectives to simulate the dynamics of information diffusion over crowds with underlying social relationships. Existing works [Chao 2009; Neumann 2000] model the communications between agents so that elicited emotions can be spread in the space while others (e.g. [Kempe 2003]) study how information diffuses over a social network. However, the former considers only spatial aspects and the latter utilizes only the social relationships. To combine both spatial and social aspects for diffusion, we propose a framework, CrowDiffuse, which simulates the crowd with an underlying social network and allows information to propagate over agents. In CrowDiffuse, agents can affect each other if they satisfy both spatial and social condition. The spatial condition is satisfied if two agents come close enough in the space while the social condition is met if two agents possess a relationship in the social network. In addition, we further investigate the targeted diffusion problem, which will be described in the following.