Table 5.

Logit regression: reaction likelihood.

	Dependent variable: Reaction likelihood*
	Model A	Model B	Model C	Model D	Model E	Model F
Perceived veracity: misleading	−0.42***	−0.43***	−0.40***	−0.40***	−0.37***	−0.43***
	(0.08)	(0.09)	(0.11)	(0.11)	(0.09)	(0.10)
Perceived veracity: fake	−0.46***	−0.54***	−0.35**	−0.35**	−0.27**	−0.33**
	(0.09)	(0.12)	(0.17)	(0.17)	(0.14)	(0.16)
Misleading news	0.15**	0.51*		0.52	0.09	0.01
	(0.07)	(0.31)		(0.37)	(0.15)	(0.17)
Fake news	0.72***	0.12		−0.32	0.31*	0.38**
	(0.10)	(0.31)		(0.35)	(0.16)	(0.18)
Perceived veracity*misleading news			−0.01	−0.01	0.04	0.14
			(0.13)	(0.13)	(0.10)	(0.11)
Perceived veracity* fake news			0.56***	0.56***	0.46***	0.61***
			(0.16)	(0.16)	(0.13)	(0.16)
Participant fixed effects	No	Yes	Yes	Yes	No	Yes
Tweet fixed effects	No	Yes	Yes	Yes	No	No
Control variables	No	No	No	No	Yes	No
Constant	−0.30***	−2.02***	−2.07***	−2.07***	−0.39***	−2.33***
	(0.06)	(0.66)	(0.66)	(0.66)	(0.07)	(0.62)
Observations	3,872	3,872	3,872	3,872	3,872	3,872
Log likelihood	−2576.12	−1922.59	−1915.72	−1915.72	−2522.41	−2045.68
Akaike inf. Crit.	5162.24	4153.18	4143.43	4143.43	5072.82	4345.37

^*p<0.1;

^**p<0.05;

^***p<0.01.

^*A reaction is defined as any combination or use of likes, retweets, and comments.

Analysis of the data was done using the stargazer package (Hlavac, 2018).