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Psychological Language on Twitter Predicts County-Level Heart Disease Mortality.

Overview of attention for article published in Psychological Science (Sage Publications Inc.), January 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#10 of 3,341)
  • 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
42 news outlets
blogs
17 blogs
twitter
1097 tweeters
peer_reviews
1 peer review site
weibo
2 weibo users
facebook
17 Facebook pages
googleplus
2 Google+ users
reddit
1 Redditor

Readers on

mendeley
371 Mendeley
Title
Psychological Language on Twitter Predicts County-Level Heart Disease Mortality.
Published in
Psychological Science (Sage Publications Inc.), January 2015
DOI 10.1177/0956797614557867
Pubmed ID
Authors

Johannes C. Eichstaedt, Hansen Andrew Schwartz, Margaret L. Kern, Gregory Park, Darwin R. Labarthe, Raina M. Merchant, Sneha Jha, Megha Agrawal, Lukasz A. Dziurzynski, Maarten Sap, Christopher Weeg, Emily E. Larson, Lyle H. Ungar, Martin E. P. Seligman, Eichstaedt JC, Schwartz HA, Kern ML, Park G, Labarthe DR, Merchant RM, Jha S, Agrawal M, Dziurzynski LA, Sap M, Weeg C, Larson EE, Ungar LH, Seligman ME, Johannes C. Eichstaed

Abstract

Hostility and chronic stress are known risk factors for heart disease, but they are costly to assess on a large scale. We used language expressed on Twitter to characterize community-level psychological correlates of age-adjusted mortality from atherosclerotic heart disease (AHD). Language patterns reflecting negative social relationships, disengagement, and negative emotions-especially anger-emerged as risk factors; positive emotions and psychological engagement emerged as protective factors. Most correlations remained significant after controlling for income and education. A cross-sectional regression model based only on Twitter language predicted AHD mortality significantly better than did a model that combined 10 common demographic, socioeconomic, and health risk factors, including smoking, diabetes, hypertension, and obesity. Capturing community psychological characteristics through social media is feasible, and these characteristics are strong markers of cardiovascular mortality at the community level.

Twitter Demographics

The data shown below were collected from the profiles of 1,097 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 371 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 19 5%
United Kingdom 6 2%
Canada 3 <1%
Australia 2 <1%
Taiwan 2 <1%
Netherlands 2 <1%
Sweden 2 <1%
Spain 2 <1%
Germany 1 <1%
Other 7 2%
Unknown 325 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 90 24%
Student > Master 69 19%
Researcher 62 17%
Student > Doctoral Student 27 7%
Student > Bachelor 22 6%
Other 101 27%
Readers by discipline Count As %
Psychology 138 37%
Computer Science 56 15%
Social Sciences 34 9%
Medicine and Dentistry 32 9%
Unspecified 30 8%
Other 81 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 977. 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 03 June 2018.
All research outputs
#2,778
of 11,403,309 outputs
Outputs from Psychological Science (Sage Publications Inc.)
#10
of 3,341 outputs
Outputs of similar age
#84
of 251,688 outputs
Outputs of similar age from Psychological Science (Sage Publications Inc.)
#1
of 52 outputs
Altmetric has tracked 11,403,309 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 3,341 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 57.5. 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 251,688 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 52 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.