Fig. 4 Spatial distributions and mutual correlations between Hurricane Sandy damage, Twitter activity, and average sentiment of tweets. Spatial distributions.

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Presentation transcript:

Fig. 4 Spatial distributions and mutual correlations between Hurricane Sandy damage, Twitter activity, and average sentiment of tweets. Spatial distributions and mutual correlations between Hurricane Sandy damage, Twitter activity, and average sentiment of tweets. Correlations between per-capita Twitter activity and damage are illustrated at the ZCTA level for New Jersey (A) and at the county level for New Jersey and New York (B). The difference in geographic coverage is dictated by the quality of data: no insurance data are available for New York at the ZCTA level. Spatial distributions show that both variables reach their highest levels along the coast and in densely populated metropolitan areas around New York City. Normalized activity and damage both follow a quasi log-normal distribution [see the histograms along the axes of the scatter plot in (A)]. A moderately strong positive correlation between postlandfall activity and damage is observed, especially for fine-resolution analysis [see inset tables in the scatter plots in (A) and (B) for exact statistics and P values]. Sentiment-versus-damage (S-D) analysis is underpowered at the ZCTA level (τ = −0.031, P = 0.29), but county-level analysis shows that negative sentiment correlates with damage (τ = −0.28, P = 0.018). Yury Kryvasheyeu et al. Sci Adv 2016;2:e1500779 Copyright © 2016, The Authors