Table 3 Detecting and sharing fake news by country.

From: Ability of detecting and willingness to share fake news

 

Detecting fake news

Sharing fake news

(1)

(2)

(3)

(4)

Germany

UK

Germany

UK

Female (ref:male)

− 1.187***

− 0.451*

− 0.051

− 0.408**

(0.199)

(0.202)

(0.090)

(0.125)

Age

0.044***

0.021*

− 0.011**

− 0.040***

(0.008)

(0.009)

(0.004)

(0.006)

High educated (ref:low edu)

0.544*

0.028

− 0.157+

− 0.037

(0.212)

(0.205)

(0.087)

(0.128)

Separated/Single (ref:married/coh)

0.187

0.207

− 0.038

− 0.204

(0.220)

(0.220)

(0.097)

(0.130)

Middle income (ref:low)

0.131

0.499*

− 0.007

− 0.047

(0.287)

(0.237)

(0.124)

(0.142)

High income (ref:low)

0.880*

0.954**

− 0.132

− 0.062

(0.386)

(0.326)

(0.157)

(0.195)

Unemployed (ref:employed)

− 1.131

0.062

0.599

− 0.441

(0.840)

(0.748)

(0.635)

(0.375)

Out of labor force (ref:employed)

− 0.024

0.197

− 0.112

− 0.116

(0.271)

(0.237)

(0.099)

(0.132)

Center (ref:left)

− 0.602*

− 0.889***

0.006

0.346*

(0.252)

(0.261)

(0.099)

(0.143)

Right (ref:left)

− 0.372

− 1.027**

0.320+

1.027***

(0.352)

(0.314)

(0.169)

(0.199)

Constant

22.031***

22.050***

1.273***

3.111***

(0.609)

(0.601)

(0.255)

(0.414)

N

1223

1156

1223

1156

Adj. R-sq

0.070

0.021

0.015

0.074

  1. All estimates are from linear models estimated by Ordinary Least Squares. HC1 robust standard errors are in parentheses. + p \(<0.10\), * p \(<0.05\), ** p \(<0.01\), *** p \(<0.001\) (two-tailed tests).