Research in the field of collective intelligence is currently focused mainly on determining ways to provide a more and more accurate prediction. However, the development of collective intelligence requires a more formal approach. Thus the natural next step is to introduce the formal model of collective. Many scientists seem to see this need, but available solutions usually focus on narrow specialization. The problems within the scope of collective intelligence field typically require complex models. Sometimes more than one model has to be used. This paper addresses both issues. Authors introduce graph-based meta-model of collective that intend to describe all collective’s properties based on psychological knowledge, especially on Surowiecki’s work. Moreover, we introduced the taxonomy of metrics that allow assessing the qualitative aspects of crowd’s structure and dynamics.
CITATION STYLE
Jodłowiec, M., Krótkiewicz, M., Palak, R., & Wojtkiewicz, K. (2019). Graph-based crowd definition for assessing wise crowd measures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11683 LNAI, pp. 66–78). Springer Verlag. https://doi.org/10.1007/978-3-030-28377-3_6
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