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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
90 news outlets
blogs
7 blogs
twitter
4385 tweeters
facebook
8 Facebook pages
googleplus
2 Google+ users

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
157 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 4,385 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 157 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 157 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 22%
Researcher 26 17%
Student > Master 22 14%
Student > Bachelor 21 13%
Unspecified 20 13%
Other 34 22%
Readers by discipline Count As %
Psychology 38 24%
Unspecified 31 20%
Computer Science 22 14%
Social Sciences 15 10%
Agricultural and Biological Sciences 11 7%
Other 40 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 1323. 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 19 July 2019.
All research outputs
#2,015
of 13,243,675 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#81
of 79,759 outputs
Outputs of similar age
#113
of 262,198 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#5
of 955 outputs
Altmetric has tracked 13,243,675 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 79,759 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.6. 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 262,198 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 955 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.