ArticleProceedings of the National Academy of Sciences of the United States of America2015
Crowd science user contribution patterns and their implications.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
48 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Hoping for optimality or designing for inclusion: Persistence, learning, and the social network of citizen science.Proceedings of the National Academy of Sciences of the United States of America · 2019Pooled it
- Harnessing Citizen Science to Support Nature-Based Flood Management: A Case Study of Photo Post Engagement in the Limb Brook Catchment, Sheffield, UK.Environmental management · 2026Article
- Citizen Science Quickly Reveals the Argentine Ant Linepithema humile (Mayr, 1868) Distribution in an Invaded Urban Area and Provides Unexpected Findings.Neotropical entomology · 2025Article
- LIFE 4 Pollinators' platform: How citizen science can help monitoring plants and pollinators.AoB PLANTS · 2025Article
- Crowdsourcing conservation: unveiling Taiwan's sea turtle foraging grounds, emerging threats, and residency with broad societal engagement.BMC ecology and evolution · 2025Article
- The academic impact of Open Science: a scoping review.Royal Society open science · 2025Review
- A super SDM (species distribution model) 'in the cloud' for better habitat-association inference with a 'big data' application of the Great Gray Owl for Alaska.Scientific reports · 2024Article
- Article
- Quantifying online citizen science: Dynamics and demographics of public participation in science.PloS one · 2023Article
- A game-theoretic analysis of Wikipedia's peer production: The interplay between community's governance and contributors' interactions.PloS one · 2023Article
- Eight years of community structure monitoring through recreational citizen science at the "SS Thistlegorm" wreck (Red Sea).PloS one · 2023Article
- Article
- Understanding the Inequality of Web Traffic and Engagement in Online Healthcare Communities.Frontiers in public health · 2022Article
- Article
- Article
- A community-powered search of machine learning strategy space to find NMR property prediction models.PloS one · 2021Article
- Camera settings and biome influence the accuracy of citizen science approaches to camera trap image classification.Ecology and evolution · 2020Article
- Research data management in health and biomedical citizen science: practices and prospects.JAMIA open · 2020Article
- Applying citizen science to monitor for the Sustainable Development Goal Indicator 6.3.2: a review.Environmental monitoring and assessment · 2020Review
- Applying citizen science to gene, drug and disease relationship extraction from biomedical abstracts.Bioinformatics (Oxford, England) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Scientific research performed with the involvement of the broader public (the crowd) attracts increasing attention from scientists and policy makers. A key premise is that project organizers may be able to draw on underused human resources to advance research at relatively low cost. Despite a growing number of examples, systematic research on the effort contributions volunteers are willing to make to crowd science projects is lacking. Analyzing data on seven different projects, we quantify the financial value volunteers can bring by comparing their unpaid contributions with counterfactual costs in traditional or online labor markets. The volume of total contributions is substantial, although some projects are much more successful in attracting effort than others. Moreover, contributions received by projects are very uneven across time--a tendency toward declining activity is interrupted by spikes typically resulting from outreach efforts or media attention. Analyzing user-level data, we find that most contributors participate only once and with little effort, leaving a relatively small share of users who return responsible for most of the work. Although top contributor status is earned primarily through higher levels of effort, top contributors also tend to work faster. This speed advantage develops over multiple sessions, suggesting that it reflects learning rather than inherent differences in skills. Our findings inform recent discussions about potential benefits from crowd science, suggest that involving the crowd may be more effective for some kinds of projects than others, provide guidance for project managers, and raise important questions for future research.
Indexed as
Identifiers
What OpenQuestion holds
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.