ArticleScientific reports2015
Modeling crowdsourcing as collective problem solving.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Group formation on a small-world: experiment and modelling.Journal of the Royal Society, Interface · 2019Trial
- Self-organization in Slovenian public spending.Royal Society open science · 2023Article
- Human-agent coordination in a group formation game.Scientific reports · 2021Article
- How to specify healthcare process improvements collaboratively using rapid, remote consensus-building: a framework and a case study of its application.BMC medical research methodology · 2021Article
- Article
- Humans best judge how much to cooperate when facing hard problems in large groups.Scientific reports · 2019Article
- Robust clustering of languages across Wikipedia growth.Royal Society open science · 2017Article
- Scientific crowdsourcing in wildlife research and conservation: Tigers (Panthera tigris) as a case study.PLoS biology · 2017Article
- Mitigating Herding in Hierarchical Crowdsourcing Networks.Scientific reports · 2016Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.