Adaptive social networks promote the wisdom of crowds
- Submitting institution
-
University of Oxford
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11604
- Type
- D - Journal article
- DOI
-
-
- Title of journal
- Proceedings of the National Academy of Sciences
- Article number
- -
- First page
- 11379
- Volume
- 117
- Issue
- 21
- ISSN
- 0027-8424
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.1917687117/-/DCSupplemental
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
-
- Citation count
- 5
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Drawing on organization science, biology, and CS, this work leveraged a bespoke codebase for multi-participant behavioural experiments in order to contribute to a key question about collective intelligence: under what conditions does social interaction undermine or promote the wisdom of crowds? The paper deploys a computational model to validate and explore the mechanisms discovered. The work was covered by WFMZ News (http://tiny.cc/fdxyqz), Yahoo News (http://tiny.cc/ydxyqz), Yahoo Finance (http://tiny.cc/kexyqz), and Business Insider (http://tiny.cc/yexyqz). Code and data for replication are openly available at https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/EOYZKH.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -