Collective intelligence: analysis and modelling
Authored by Roberto Zarama, Valencia Erika Suarez, Victor Bucheli, Angel Garcia
Date Published: 2015
DOI: 10.1108/k-11-2014-0245
Sponsors:
No sponsors listed
Platforms:
NetLogo
Model Documentation:
Other Narrative
Model Code URLs:
Model code not found
Abstract
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, Bogota, 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.
Tags