Public risk perception and emotion on Twitter during the Covid-19 pandemic

Applied Network Science

Table 4 The results from the fit of a power law [see Eq. (11)] to the relationship between the Death NLS and the national daily death count

Power law	\(\beta\)	\(\nu\)	95% CI	\(t\)	\(P>\|t\|\)	\(R^2\)*	NRMSE	\(n\)
Country			(\(\beta\))	(\(\beta\))	(\(\beta\))
Argentina	0.164	2.21	0.121–0.208	7.59	0.0	0.411	0.114	75
Australia	0.363	0.99	0.181–0.546	4.02	0.0002	0.259	0.173	43
Canada	0.288	0.37	0.252–0.323	16.29	0.0	0.678	0.106	87
Chile	0.085	2.47	0.06–0.109	6.97	0.0	0.382	0.151	78
Colombia	0.112	1.81	0.083–0.142	7.57	0.0	0.425	0.143	75
India	0.126	0.77	0.101–0.15	10.33	0.0	0.558	0.126	81
Mexico	0.141	1.52	0.126–0.157	18.04	0.0	0.78	0.1	78
Nigeria	0.104	1.56	0.037–0.172	3.09	0.0031	0.143	0.223	60
South Africa	0.087	1.11	0.037–0.136	3.52	0.0008	0.16	0.184	66
Spain	0.014	2.14	− 0.03 to 0.059	0.64	0.5241	− 0.042	0.202	82
UK	0.356	0.16	0.302–0.409	13.21	0.0	0.514	0.149	91
USA	0.309	0.21	0.279–0.339	20.54	0.0	0.608	0.139	88

This is the best model in some cases, though it is outperformed by the Weber–Fechner law most times. *While we fit this model assuming a log-log relationship between p and s, we compute \(R^2\) with linear p to make it comparable to the model implied by the Weber–Fechner law [see Eq. (14) in “Appendix 1” for details]. This may cause negative values of \(R^2\) as is the case for Spain