Detecting Influence in Wisdom of the Crowds

Luís Correia, Sofia Silva, Ana Cristina B. Garcia

2018

Abstract

The wisdom of the crowds effect (WoC) is a collective intelligence (CI) property by which, given a problem, a crowd is able to provide a solution better than that of any of its individuals. However, WoC is considered to require that participants are not priorly influenced by information received on the subject of the problem. Therefore it is important to have metrics that can identify the presence of influence in an experiment, so that who runs it can decide if the outcome is product of the WoC or of a cascade of individuals influencing others. In this paper we provide a set of metrics that can analyse a WoC experiment as a data stream and produce a clear indication of the presence of some influence. The results presented were obtained with real data from different information conditions, and are encouraging. The paper concludes with a discussion of relevant situations and points the most important steps that follow in this research.

Paper Citation

in Harvard Style

Correia L., Silva S. and Garcia A. (2018). Detecting Influence in Wisdom of the Crowds.In Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-275-2, pages 17-24. DOI: 10.5220/0006551200170024

in Bibtex Style

@conference{icaart18,
author={Luís Correia and Sofia Silva and Ana Cristina B. Garcia},
title={Detecting Influence in Wisdom of the Crowds},
booktitle={Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2018},
pages={17-24},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006551200170024},
isbn={978-989-758-275-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Detecting Influence in Wisdom of the Crowds
SN - 978-989-758-275-2
AU - Correia L.
AU - Silva S.
AU - Garcia A.
PY - 2018
SP - 17
EP - 24
DO - 10.5220/0006551200170024