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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
  • Among the highest-scoring outputs from this source (#18 of 139,235)
  • 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)

Mentioned by

news
36 news outlets
blogs
17 blogs
twitter
1643 tweeters
patent
1 patent
facebook
94 Facebook pages
wikipedia
2 Wikipedia pages
googleplus
78 Google+ users
reddit
5 Redditors
video
2 video uploaders

Citations

dimensions_citation
344 Dimensions

Readers on

mendeley
2370 Mendeley
citeulike
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

The data shown below were collected from the profiles of 1,643 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 2,370 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 43 2%
China 12 <1%
United Kingdom 11 <1%
Germany 11 <1%
Brazil 9 <1%
Spain 7 <1%
France 6 <1%
India 6 <1%
Japan 6 <1%
Other 61 3%
Unknown 2198 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 616 26%
Student > Master 605 26%
Researcher 312 13%
Student > Bachelor 298 13%
Unspecified 128 5%
Other 411 17%
Readers by discipline Count As %
Computer Science 1641 69%
Unspecified 178 8%
Engineering 149 6%
Mathematics 65 3%
Business, Management and Accounting 50 2%
Other 287 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 1781. 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 24 January 2019.
All research outputs
#913
of 12,844,464 outputs
Outputs from PLoS ONE
#18
of 139,235 outputs
Outputs of similar age
#13
of 161,513 outputs
Outputs of similar age from PLoS ONE
#2
of 3,975 outputs
Altmetric has tracked 12,844,464 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 139,235 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.8. 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 161,513 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 3,975 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.