Social Collective as a Modular Group Modeling Tool - Marcin Maleszka (IEEE Access)
This paper presents a comprehensive description of the social collective, an approach to group modeling for computational collective intelligence purposes. The social collective is independent of the structure of connections between members of the group, therefore it may use any existing representation of a social graph as a basis. Its modular form describes the internal mechanisms of group members: what type of data or knowledge do they use, how is it modified based on internal factors and on communication, as well as how communication between members works. A measure of drift is described in several variants, to better represent the behavior of the social collective. The measure is derived from behavior of social groups and past multi-agent models. Simulation experiments are used to show the observable effects in terms of drift, and to compare to non-collective approaches to group modeling. Social collective is specialized for computational collective intelligence tasks, but it may be fine-tuned for classical tasks, e.g., knowledge diffusion.