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 (#9 of 43,980)
  • 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)

Readers on

mendeley
1251 Mendeley
citeulike
27 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

Michal Kosinski, David Stillwell, Thore Graepel, Kosinski, Michal, Stillwell, David, Graepel, Thore

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 1,466 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 1,251 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 63 5%
United Kingdom 33 3%
Germany 26 2%
France 10 <1%
Australia 9 <1%
Spain 9 <1%
Brazil 8 <1%
Japan 7 <1%
Finland 6 <1%
Other 70 6%
Unknown 1010 81%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 349 28%
Student > Master 242 19%
Researcher 216 17%
Student > Bachelor 93 7%
Other 74 6%
Other 277 22%
Readers by discipline Count As %
Computer Science 357 29%
Psychology 257 21%
Social Sciences 174 14%
Agricultural and Biological Sciences 105 8%
Business, Management and Accounting 79 6%
Other 279 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 2029. 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 20 March 2017.
All research outputs
#219
of 7,430,852 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#9
of 43,980 outputs
Outputs of similar age
#4
of 114,517 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#1
of 983 outputs
Altmetric has tracked 7,430,852 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 43,980 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.3. 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 114,517 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 983 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.