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Article Metrics

Facebook language predicts depression in medical records

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, October 2018
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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)

Mentioned by

news
97 news outlets
blogs
9 blogs
policy
1 policy source
twitter
3990 tweeters
facebook
11 Facebook pages
googleplus
2 Google+ users

Citations

dimensions_citation
52 Dimensions

Readers on

mendeley
281 Mendeley
Title
Facebook language predicts depression in medical records
Published in
Proceedings of the National Academy of Sciences of the United States of America, October 2018
DOI 10.1073/pnas.1802331115
Pubmed ID
Authors

Johannes C. Eichstaedt, Robert J. Smith, Raina M. Merchant, Lyle H. Ungar, Patrick Crutchley, Daniel Preoţiuc-Pietro, David A. Asch, H. Andrew Schwartz

Twitter Demographics

The data shown below were collected from the profiles of 3,990 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 281 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 281 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 54 19%
Researcher 42 15%
Student > Master 42 15%
Student > Bachelor 40 14%
Student > Doctoral Student 18 6%
Other 37 13%
Unknown 48 17%
Readers by discipline Count As %
Psychology 56 20%
Computer Science 40 14%
Medicine and Dentistry 21 7%
Social Sciences 21 7%
Agricultural and Biological Sciences 14 5%
Other 60 21%
Unknown 69 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 1384. 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 12 May 2020.
All research outputs
#2,847
of 15,184,279 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#115
of 84,519 outputs
Outputs of similar age
#113
of 273,232 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#5
of 959 outputs
Altmetric has tracked 15,184,279 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 84,519 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.8. 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 273,232 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 959 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.