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Private traits and attributes are predictable from digital records of human behavior

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, March 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#8 of 79,113)
  • 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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674 Dimensions

Readers on

mendeley
2025 Mendeley
citeulike
28 CiteULike
Title
Private traits and attributes are predictable from digital records of human behavior
Published in
Proceedings of the National Academy of Sciences of the United States of America, March 2013
DOI 10.1073/pnas.1218772110
Pubmed ID
Authors

M. Kosinski, D. Stillwell, T. Graepel

Abstract

We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender. The analysis presented is based on a dataset of over 58,000 volunteers who provided their Facebook Likes, detailed demographic profiles, and the results of several psychometric tests. The proposed model uses dimensionality reduction for preprocessing the Likes data, which are then entered into logistic/linear regression to predict individual psychodemographic profiles from Likes. The model correctly discriminates between homosexual and heterosexual men in 88% of cases, African Americans and Caucasian Americans in 95% of cases, and between Democrat and Republican in 85% of cases. For the personality trait "Openness," prediction accuracy is close to the test-retest accuracy of a standard personality test. We give examples of associations between attributes and Likes and discuss implications for online personalization and privacy.

Twitter Demographics

The data shown below were collected from the profiles of 1,715 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 2,025 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 56 3%
United Kingdom 33 2%
Germany 29 1%
France 10 <1%
Brazil 10 <1%
Spain 8 <1%
Australia 8 <1%
Finland 6 <1%
Austria 6 <1%
Other 68 3%
Unknown 1791 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 492 24%
Student > Master 398 20%
Researcher 313 15%
Student > Bachelor 191 9%
Student > Doctoral Student 121 6%
Other 506 25%
Unknown 4 <1%
Readers by discipline Count As %
Computer Science 468 23%
Psychology 365 18%
Social Sciences 287 14%
Unspecified 183 9%
Business, Management and Accounting 153 8%
Other 565 28%
Unknown 4 <1%

Attention Score in Context

This research output has an Altmetric Attention Score of 3338. 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 14 May 2019.
All research outputs
#176
of 12,979,240 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#8
of 79,113 outputs
Outputs of similar age
#4
of 144,049 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#1
of 1,007 outputs
Altmetric has tracked 12,979,240 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 79,113 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.2. 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 144,049 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 1,007 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.