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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 (98th percentile)

Mentioned by

news
72 news outlets
blogs
5 blogs
twitter
430 tweeters
facebook
8 Facebook pages
googleplus
2 Google+ users

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
85 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 430 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 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 85 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 24%
Researcher 16 19%
Unspecified 14 16%
Student > Doctoral Student 10 12%
Student > Master 9 11%
Other 16 19%
Readers by discipline Count As %
Psychology 24 28%
Unspecified 17 20%
Social Sciences 10 12%
Computer Science 8 9%
Agricultural and Biological Sciences 6 7%
Other 20 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 894. 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 06 January 2019.
All research outputs
#4,071
of 12,358,148 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#166
of 77,495 outputs
Outputs of similar age
#219
of 251,338 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#10
of 969 outputs
Altmetric has tracked 12,358,148 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 77,495 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.1. 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 251,338 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 969 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 98% of its contemporaries.