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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.
doi 10.7717/peerj.5656/fig-2
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Figure 1: Twitter Topics Highly Correlated With Age-Adjusted Mortality From Self-Harm, Cf. Eichstaedt Et Al.’s (2015a).
Does Twitter Language Reliably Predict Heart Disease? A Commentary on Eichstaedt Et Al. (2015a)
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Genetics
Molecular Biology
Biochemistry
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Medicine
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Figure 3: Comparison of Observed and Predicted Mortality From the Analysis of Prefectural Data.
Figure 3: Phylogenetic Trees From the Analyses of (A) Butler Et Al. (2014); (B) Kammerer Et Al. (2015).
Figure 3: Results of the Analysis of the H3Kme3 Data From Galonska Et Al. (2015).
Figure 2: Calcification Rates.
Figure 3: Predicted Probability of Epizootic Animal Plague.
Table 2: Partial Correlations Between Atherosclerotic Heart Disease (AHD) Mortality and Twitter Language Measured by Dictionaries, Across the Northern and Southern Halves of the United States.
File S1: Figure From Van Tussenbroek Et Al., 2017
