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Modeling crowdsourcing as collective problem solving

Crowdsourcing is a process of accumulating the ideas, thoughts or information from many independent participants, with aim to find the best solution for a given challenge. Modern information technologies allow for massive number of subjects to be involved in a more or less spontaneous way. Still, th...

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Detalles Bibliográficos
Autores principales: Guazzini, Andrea, Vilone, Daniele, Donati, Camillo, Nardi, Annalisa, Levnajić, Zoran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4639727/
https://www.ncbi.nlm.nih.gov/pubmed/26552943
http://dx.doi.org/10.1038/srep16557
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author Guazzini, Andrea
Vilone, Daniele
Donati, Camillo
Nardi, Annalisa
Levnajić, Zoran
author_facet Guazzini, Andrea
Vilone, Daniele
Donati, Camillo
Nardi, Annalisa
Levnajić, Zoran
author_sort Guazzini, Andrea
collection PubMed
description Crowdsourcing is a process of accumulating the ideas, thoughts or information from many independent participants, with aim to find the best solution for a given challenge. Modern information technologies allow for massive number of subjects to be involved in a more or less spontaneous way. Still, the full potentials of crowdsourcing are yet to be reached. We introduce a modeling framework through which we study the effectiveness of crowdsourcing in relation to the level of collectivism in facing the problem. Our findings reveal an intricate relationship between the number of participants and the difficulty of the problem, indicating the optimal size of the crowdsourced group. We discuss our results in the context of modern utilization of crowdsourcing.
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spelling pubmed-46397272015-12-02 Modeling crowdsourcing as collective problem solving Guazzini, Andrea Vilone, Daniele Donati, Camillo Nardi, Annalisa Levnajić, Zoran Sci Rep Article Crowdsourcing is a process of accumulating the ideas, thoughts or information from many independent participants, with aim to find the best solution for a given challenge. Modern information technologies allow for massive number of subjects to be involved in a more or less spontaneous way. Still, the full potentials of crowdsourcing are yet to be reached. We introduce a modeling framework through which we study the effectiveness of crowdsourcing in relation to the level of collectivism in facing the problem. Our findings reveal an intricate relationship between the number of participants and the difficulty of the problem, indicating the optimal size of the crowdsourced group. We discuss our results in the context of modern utilization of crowdsourcing. Nature Publishing Group 2015-11-10 /pmc/articles/PMC4639727/ /pubmed/26552943 http://dx.doi.org/10.1038/srep16557 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Guazzini, Andrea
Vilone, Daniele
Donati, Camillo
Nardi, Annalisa
Levnajić, Zoran
Modeling crowdsourcing as collective problem solving
title Modeling crowdsourcing as collective problem solving
title_full Modeling crowdsourcing as collective problem solving
title_fullStr Modeling crowdsourcing as collective problem solving
title_full_unstemmed Modeling crowdsourcing as collective problem solving
title_short Modeling crowdsourcing as collective problem solving
title_sort modeling crowdsourcing as collective problem solving
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4639727/
https://www.ncbi.nlm.nih.gov/pubmed/26552943
http://dx.doi.org/10.1038/srep16557
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