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Computer-based personality judgments are more accurate than those made by humans

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, January 2015
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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 (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Citations

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633 Dimensions

Readers on

mendeley
1751 Mendeley
citeulike
3 CiteULike
Title
Computer-based personality judgments are more accurate than those made by humans
Published in
Proceedings of the National Academy of Sciences of the United States of America, January 2015
DOI 10.1073/pnas.1418680112
Pubmed ID
Authors

Wu Youyou, Michal Kosinski, David Stillwell

Abstract

Judging others' personalities is an essential skill in successful social living, as personality is a key driver behind people's interactions, behaviors, and emotions. Although accurate personality judgments stem from social-cognitive skills, developments in machine learning show that computer models can also make valid judgments. This study compares the accuracy of human and computer-based personality judgments, using a sample of 86,220 volunteers who completed a 100-item personality questionnaire. We show that (i) computer predictions based on a generic digital footprint (Facebook Likes) are more accurate (r = 0.56) than those made by the participants' Facebook friends using a personality questionnaire (r = 0.49); (ii) computer models show higher interjudge agreement; and (iii) computer personality judgments have higher external validity when predicting life outcomes such as substance use, political attitudes, and physical health; for some outcomes, they even outperform the self-rated personality scores. Computers outpacing humans in personality judgment presents significant opportunities and challenges in the areas of psychological assessment, marketing, and privacy.

Twitter Demographics

The data shown below were collected from the profiles of 1,266 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 1,751 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 24 1%
United Kingdom 15 <1%
Germany 9 <1%
Australia 5 <1%
Brazil 5 <1%
Spain 4 <1%
Austria 3 <1%
Finland 3 <1%
Turkey 2 <1%
Other 26 1%
Unknown 1655 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 345 20%
Student > Master 276 16%
Student > Bachelor 222 13%
Researcher 188 11%
Student > Doctoral Student 98 6%
Other 366 21%
Unknown 256 15%
Readers by discipline Count As %
Psychology 438 25%
Computer Science 254 15%
Social Sciences 166 9%
Business, Management and Accounting 143 8%
Engineering 57 3%
Other 339 19%
Unknown 354 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 2688. 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 26 January 2023.
All research outputs
#2,305
of 23,039,416 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#73
of 98,711 outputs
Outputs of similar age
#19
of 353,767 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#2
of 946 outputs
Altmetric has tracked 23,039,416 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 98,711 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.1. This one has done particularly well, scoring higher than 99% 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 353,767 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 99% of its contemporaries.
We're also able to compare this research output to 946 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 99% of its contemporaries.