Table 5.

Linear regression models on predictors of likes and reposts (N=36,424).

Variables			Logarithm
			Like count+1a,b			Repost count+1a,c
			Standard β	P value	Standard β		P value
Content features
	Post topic
		Topic 1: HIV and COVID-19	−.003	.68	−.042		<.001
		Topic 2: mRNAd HIV vaccine trials	−.039	<.001	.018		.02
		Topic 3: HIV vaccine and immunity	−.910e	<.001	−.960e		<.001
	Post valence		.034	<.001	.033		<.001
Account features
	Account verification status		.234	<.001	.239		<.001
	Follower count		.095	<.001	.114		<.001

^aThe natural logarithm, ln (Y_i+1), was calculated on like and repost counts. This transformation was conducted to include posts receiving 0 likes and reposts, as well as to account for the skewness of the data distribution.

^bF (model significance): P<.001; adjusted R²=0.072.

^cF (model significance): P<.001; adjusted R²=0.090.

^dmRNA: messenger RNA.

^eThe models excluded topic 3 on HIV vaccine and immunity to address multicollinearity issues arising from its correlations with topics 1 and 2. The reported standard β for topic 3 represents a possible β value if it had been included in the models.