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Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach

Overview of attention for article published in PLOS ONE, September 2013
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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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981 Dimensions

Readers on

mendeley
2387 Mendeley
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9 CiteULike
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Title
Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach
Published in
PLOS ONE, September 2013
DOI 10.1371/journal.pone.0073791
Pubmed ID
Authors

H. Andrew Schwartz, Johannes C. Eichstaedt, Margaret L. Kern, Lukasz Dziurzynski, Stephanie M. Ramones, Megha Agrawal, Achal Shah, Michal Kosinski, David Stillwell, Martin E. P. Seligman, Lyle H. Ungar

Abstract

We analyzed 700 million words, phrases, and topic instances collected from the Facebook messages of 75,000 volunteers, who also took standard personality tests, and found striking variations in language with personality, gender, and age. In our open-vocabulary technique, the data itself drives a comprehensive exploration of language that distinguishes people, finding connections that are not captured with traditional closed-vocabulary word-category analyses. Our analyses shed new light on psychosocial processes yielding results that are face valid (e.g., subjects living in high elevations talk about the mountains), tie in with other research (e.g., neurotic people disproportionately use the phrase 'sick of' and the word 'depressed'), suggest new hypotheses (e.g., an active life implies emotional stability), and give detailed insights (males use the possessive 'my' when mentioning their 'wife' or 'girlfriend' more often than females use 'my' with 'husband' or 'boyfriend'). To date, this represents the largest study, by an order of magnitude, of language and personality.

Twitter Demographics

Twitter Demographics

The data shown below were collected from the profiles of 1,417 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2,387 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 31 1%
United Kingdom 15 <1%
Germany 6 <1%
Russia 5 <1%
Spain 4 <1%
Indonesia 4 <1%
Brazil 4 <1%
France 3 <1%
Australia 3 <1%
Other 31 1%
Unknown 2281 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 405 17%
Student > Master 284 12%
Student > Bachelor 202 8%
Researcher 194 8%
Student > Doctoral Student 102 4%
Other 310 13%
Unknown 890 37%
Readers by discipline Count As %
Computer Science 382 16%
Psychology 348 15%
Social Sciences 205 9%
Business, Management and Accounting 114 5%
Linguistics 79 3%
Other 307 13%
Unknown 952 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1669. 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 21 February 2023.
All research outputs
#6,090
of 24,495,755 outputs
Outputs from PLOS ONE
#65
of 211,516 outputs
Outputs of similar age
#25
of 208,595 outputs
Outputs of similar age from PLOS ONE
#4
of 4,870 outputs
Altmetric has tracked 24,495,755 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 211,516 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.6. 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 208,595 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 4,870 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.