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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
  • Among the highest-scoring outputs from this source (#12 of 3,449)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
43 news outlets
blogs
17 blogs
twitter
1148 tweeters
peer_reviews
1 peer review site
weibo
2 weibo users
facebook
17 Facebook pages
googleplus
2 Google+ users
reddit
1 Redditor

Citations

dimensions_citation
127 Dimensions

Readers on

mendeley
395 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

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 1,148 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 395 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%
Spain 2 <1%
Taiwan 2 <1%
Sweden 2 <1%
Germany 1 <1%
Netherlands 1 <1%
Russian Federation 1 <1%
Other 6 2%
Unknown 352 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 96 24%
Student > Master 66 17%
Researcher 65 16%
Student > Bachelor 28 7%
Student > Doctoral Student 28 7%
Other 112 28%
Readers by discipline Count As %
Psychology 144 36%
Computer Science 55 14%
Unspecified 42 11%
Social Sciences 38 10%
Medicine and Dentistry 33 8%
Other 83 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 1033. 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 11 January 2019.
All research outputs
#2,969
of 12,386,546 outputs
Outputs from Psychological Science (Sage Publications Inc.)
#12
of 3,449 outputs
Outputs of similar age
#67
of 264,912 outputs
Outputs of similar age from Psychological Science (Sage Publications Inc.)
#1
of 40 outputs
Altmetric has tracked 12,386,546 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 3,449 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 61.1. 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 264,912 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 40 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 97% of its contemporaries.