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Figure 1: Twitter Topics Highly Correlated With Age-Adjusted Mortality From Self-Harm, Cf. Eichstaedt Et Al.’s (2015a).
doi 10.7717/peerj.5656/fig-1
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Figure 2: Difference Between the Two Maps of AHD Mortality Rates (CDC-reported and Twitter-Predicted) From Eichstaedt Et Al.’s (2015a) Figure 3.
Does Twitter Language Reliably Predict Heart Disease? A Commentary on Eichstaedt Et Al. (2015a)
PeerJ
Genetics
Molecular Biology
Biochemistry
Biological Sciences
Medicine
Agricultural
Neuroscience
Table 1: Correlations Between Self-Harm and Twitter Language Measured by Dictionaries.
Correction for Crockett Et Al., Harm to Others Outweighs Harm to Self in Moral Decision Making
Proceedings of the National Academy of Sciences of the United States of America
Multidisciplinary
Thorax and Abdomen Body Segment Inertial Parameters Adjusted From McConville Et Al. And Young Et Al.
International Biomechanics
Orthopedics
Sports Medicine
Physical Therapy
Computer Science Applications
Sports Therapy
Biomedical Engineering
Rehabilitation
Diabetes Topics Associated With Engagement on Twitter
Preventing chronic disease
Health Policy
Public Health
Occupational Health
Environmental
Figure 1: PRISMA Flow Diagram (Adapted From Moher Et Al., 2009).
Figure 1: Global MeIQx Metabolism Pathway (Langouët Et Al., 2001).
Figure 1: Grey Wolfs’ Hierarchal Leadership (Faris Et Al., 2018).
