Table 3. Analysis results of fixation time and fixation count on Twitter and TikTok.

	Fixation time					Fixation count
	Mean		SD	F-value	Sig.	Mean	SD	F-value	Sig.
AOI_Text	Twitter	13.8045	3.01311	.138	.712	42.5778	7.82812	.039	.845
AOI_Text	TikTok	13.3911	3.96261	.138	.712	42.0611	8.74440	.039	.845
Emotional^a	Twitter	13.8103	3.10228	.048	.828	42.1833	9.07633	.005	.942
Emotional^a	TikTok	13.5578	4.12947	.048	.828	42.4000	9.69074	.005	.942
Neutral^b	Twitter	13.7930	3.34616	.395	.534	43.3667	6.81579	.610	.440
Neutral^b	TikTok	13.0575	4.02791	.395	.534	41.3833	9.08007	.610	.440
POSITIVE^c	Twitter	12.6357	2.76291	.650	.425	38.2333	8.36248	.069	.795
POSITIVE^c	TikTok	11.8210	3.57615	.650	.425	37.5333	8.51720	.069	.795
Negative^d	Twitter	14.9848	3.88370	.046	.830	46.1333	11.14781	.100	.753
Negative^d	TikTok	15.2947	5.12283	.046	.830	47.2667	11.49961	.100	.753

N=40.
emotional is the mean of all positive and negative text.
non-emotional (Neutral)is the mean of all neutral text.
positive is the mean of all positive text.
negative is the mean of all negative text.