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International Journal of Crowd Science 2020, 4(3): 295-307 https://doi.org/10.1108/IJCS-03-2020-0008
Research paper | Open Access | Issue | Published: 02 July 2020

Meta measurement of intelligence with crowd network

Show Author's Information Zheming Yang1,  Wen Ji2( )
Institute of Computing Technology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China
Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
Keywords:
Measurement, Meta-analysis, Intelligence, Citizen science, Crowd network, Models and methods for crowd science and engineering
Cite this article:
Yang Z, Ji W. Meta measurement of intelligence with crowd network. International Journal of Crowd Science, 2020, 4(3): 295-307. https://doi.org/10.1108/IJCS-03-2020-0008
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Abstract Full text About this article
Purpose

The multiple factors of intelligence measurement are critical in intelligent science. The intelligence measurement is typically built as a model based on multiple factors. The different agent is generally difficult to measure because of the uncertainty between multiple factors. The purpose of this paper is to solve the problem of uncertainty between multiple factors and propose an effective method for universal intelligence measurement for the different agents.

Design/methodology/approach

In this paper, the authors propose a universal intelligence measurement method based on meta-analysis for crowd network. First, the authors get study data through keywords in the database and delete the low-quality data. Second, they compute the effect value by odds ratio, relative risk and risk difference. Then, they test the homogeneity by Q-test and analyze the bias by funnel plots. Third, they select the fixed effect and random effect as a statistical model. Finally, through the meta-analysis of time, complexity and reward, the weight of each factor in the intelligence measurement is obtained and then the meta measurement model is constructed.

Findings

This paper studies the relationship among time, complexity and reward through meta-analysis and effectively combines the measurement of heterogeneous agents such as human, machine, enterprise, government and institution.

Originality/value

This paper provides a universal intelligence measurement model for crowd network. And it can provide a theoretical basis for the research of crowd science.


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Abstract
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About this article

Meta measurement of intelligence with crowd network

Show Author's information Zheming Yang1, Wen Ji2( )
Institute of Computing Technology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China
Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

Abstract

Purpose

The multiple factors of intelligence measurement are critical in intelligent science. The intelligence measurement is typically built as a model based on multiple factors. The different agent is generally difficult to measure because of the uncertainty between multiple factors. The purpose of this paper is to solve the problem of uncertainty between multiple factors and propose an effective method for universal intelligence measurement for the different agents.

Design/methodology/approach

In this paper, the authors propose a universal intelligence measurement method based on meta-analysis for crowd network. First, the authors get study data through keywords in the database and delete the low-quality data. Second, they compute the effect value by odds ratio, relative risk and risk difference. Then, they test the homogeneity by Q-test and analyze the bias by funnel plots. Third, they select the fixed effect and random effect as a statistical model. Finally, through the meta-analysis of time, complexity and reward, the weight of each factor in the intelligence measurement is obtained and then the meta measurement model is constructed.

Findings

This paper studies the relationship among time, complexity and reward through meta-analysis and effectively combines the measurement of heterogeneous agents such as human, machine, enterprise, government and institution.

Originality/value

This paper provides a universal intelligence measurement model for crowd network. And it can provide a theoretical basis for the research of crowd science.

Keywords: Measurement, Meta-analysis, Intelligence, Citizen science, Crowd network, Models and methods for crowd science and engineering

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Publication history
Copyright
Acknowledgements
Rights and permissions

Publication history

Received: 07 March 2020
Revised: 13 May 2020
Accepted: 13 May 2020
Published: 02 July 2020
Issue date: September 2020

Copyright

© The author(s)

Acknowledgements

Acknowledgements

This work is supported by the National Key R&D Program of China (2017YFB1400100), and the National Natural Science Foundation of China (61572466), and the Beijing Natural Science Foundation (4162059).

Rights and permissions

Zheming Yang and Wen Ji. Published in International Journal of Crowd Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

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