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Optimal incentives for collective intelligence

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, May 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

news
5 news outlets
blogs
2 blogs
twitter
117 tweeters
facebook
3 Facebook pages
googleplus
1 Google+ user

Citations

dimensions_citation
24 Dimensions

Readers on

mendeley
145 Mendeley
citeulike
2 CiteULike
Title
Optimal incentives for collective intelligence
Published in
Proceedings of the National Academy of Sciences of the United States of America, May 2017
DOI 10.1073/pnas.1618722114
Pubmed ID
Authors

Richard P. Mann, Dirk Helbing

Abstract

Collective intelligence is the ability of a group to perform more effectively than any individual alone. Diversity among group members is a key condition for the emergence of collective intelligence, but maintaining diversity is challenging in the face of social pressure to imitate one's peers. Through an evolutionary game-theoretic model of collective prediction, we investigate the role that incentives may play in maintaining useful diversity. We show that market-based incentive systems produce herding effects, reduce information available to the group, and restrain collective intelligence. Therefore, we propose an incentive scheme that rewards accurate minority predictions and show that this produces optimal diversity and collective predictive accuracy. We conclude that real world systems should reward those who have shown accuracy when the majority opinion has been in error.

Twitter Demographics

The data shown below were collected from the profiles of 117 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 145 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
United Kingdom 1 <1%
Luxembourg 1 <1%
Belgium 1 <1%
Netherlands 1 <1%
Unknown 139 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 43 30%
Researcher 25 17%
Professor 14 10%
Student > Doctoral Student 12 8%
Student > Master 12 8%
Other 37 26%
Unknown 2 1%
Readers by discipline Count As %
Computer Science 21 14%
Unspecified 20 14%
Psychology 17 12%
Social Sciences 16 11%
Physics and Astronomy 13 9%
Other 56 39%
Unknown 2 1%

Attention Score in Context

This research output has an Altmetric Attention Score of 131. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 April 2019.
All research outputs
#113,977
of 13,531,657 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#2,702
of 80,437 outputs
Outputs of similar age
#5,251
of 284,184 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#96
of 1,009 outputs
Altmetric has tracked 13,531,657 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 80,437 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 24.1. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 284,184 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 1,009 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.