Table 5 Admitting of sharing of fake news by country.

From: Ability of detecting and willingness to share fake news

 

Admits deliberate sharing

Admits accidental sharing

(1)

(2)

(3)

(4)

Germany

UK

Germany

UK

Deliberately shared fake news

1.585***

1.733***

  

(0.203)

(0.213)

  

Accidentally shared fake news

  

1.802***

1.564***

  

(0.137)

(0.085)

Female (ref:male)

0.707

0.594*

0.568*

0.550**

(0.241)

(0.150)

(0.148)

(0.131)

Age

0.963*

0.943***

0.986

0.964***

(0.014)

(0.010)

(0.011)

(0.009)

High educated (ref:low edu)

1.722+

1.338

1.493

1.312

(0.565)

(0.326)

(0.407)

(0.294)

Separated/Single (ref:Married/Coh)

0.375*

0.669

0.622

1.077

(0.150)

(0.183)

(0.198)

(0.263)

Middle income (ref:low)

0.301**

1.104

0.354**

1.216

(0.134)

(0.389)

(0.131)

(0.406)

High income (ref:low)

0.199**

1.334

0.268*

1.282

(0.115)

(0.526)

(0.138)

(0.492)

Unemployed (ref:employed)

0.945

0.512

0.274

0.596

(1.110)

(0.595)

(0.245)

(0.624)

Out of labor force (ref:employed)

0.246*

0.955

0.492+

1.085

(0.169)

(0.316)

(0.211)

(0.333)

Center (ref:left)

0.728

0.641

0.571+

0.571+

(0.321)

(0.213)

(0.188)

(0.181)

Right (ref:left)

2.867*

1.862+

1.485

1.641

(1.280)

(0.639)

(0.532)

(0.528)

N

1223

1156

1223

1156

  1. ‘Admits deliberate sharing’ is a dummy variable given value of 1 if the respondent answered ‘yes’ to the question ‘Did you ever share a political news story online that you thought at the time was made up?’ and 0 if the respondent answered ‘no’. The variable ’admits accidental sharing’ is constructed analogously, but using the question ‘Have you ever shared a political news story online that you later found out was made up?’. The variables ‘deliberately shared fake news’ and ‘accidentally shared fake news’ are scales obtained from respondents’ assessment of headlines ranging from 0 to 5 with a higher value indicating more sharing of fake news. All estimates are from logistic regression models. The coefficients represent odds ratios. HC1 robust standard errors are in parentheses. + p \(<0.10\), * p \(<0.05\), ** p \(<0.01\), *** p \(<0.001\) (two-tailed tests).
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