TY  - JOUR
AB  - Purpose– The purpose of this paper is to focus on the underpinning dynamics that explain collective intelligence. Design/methodology/approach– Collective intelligence can be understood as the capacity of a collective system to evolve toward higher order complexity through networks of individual capacities. The authors observed two collective systems as examples of the dynamic processes of complex networks – the wiki course PeSO at the Universidad de Los Andes, Bogotá, Colombia, and an agent-based model inspired by wiki systems. Findings– The results of the wiki course PeSO and the model are contrasted with a random network baseline model. Both the wiki course and the model show dynamics of accumulation, in which statistical properties of non-equilibrium networks appear. Research limitations/implications– The work is based on network science. The authors analyzed data from two kinds of networks: the wiki course PeSO and an agent-based model. Limitations due to the number of computations and complexity appeared when there was a high order of magnitude of agents. Practical implications– Better understanding can allow for the measurement and design of systems based on collective intelligence. Originality/value– The results show how collective intelligence emerges from cumulative dynamics.
VL  - 44
IS  - 6/7
SN  - 0368-492X
DO  - 10.1108/K-11-2014-0245
UR  - https://doi.org/10.1108/K-11-2014-0245
AU  - Suárez Valencia Erika
AU  - Bucheli Víctor
AU  - Zarama Roberto
AU  - Garcia Ángel
ED  - Dr Raul Espejo
PY  - 2015
Y1  - 2015/01/01
TI  - Collective intelligence: analysis and modelling
T2  - Kybernetes
PB  - Emerald Group Publishing Limited
SP  - 1122
EP  - 1133
Y2  - 2024/05/05
ER  -