Fighting Fakes on WhatsApp—Audience Perspectives on Fact Bots as Countermeasures

Figures & data

Table 1. Interviewees.

Interview	Age	Gender	Education	Labor market position
IV 01	22	Female	High-school degree	Student
IV 02	24	Female	High-school degree	Student
IV 03	23	Female	High-school degree	Apprentice
IV 04	34	Female	University degree	Employed
IV 05	32	Female	Middle school degree	Employed
IV 06	44	Female	University degree	Employed
IV 07	55	Female	Vocational training	Employed
IV 08	78	Female	Vocational training	Employed
IV 09	55	Female	University degree	Employed
IV 10	23	Male	High-school degree	Student
IV 11	25	Male	High-school degree	Student
IV 12	33	Male	High-school degree	Student
IV 13	30	Male	High-school degree	Student
IV 14	37	Male	Vocational training	Employed
IV 15	49	Female	Vocational training	Employed
IV 16	61	Male	University degree	Employed
IV 17	57	Male	High-school degree	Entrepreneur
IV 18	57	Male	University degree	Employed

Table 2. Codes.

	Category	Subcategory
1.	Socio-demographics: gender	Male
		Female
	Socio-demographics: age cohort	18–29
		30–49
		50+
	Socio-demographics: education	Middle school degree
		High school degree
		Vocational training
		University degree
2.	Attitudes towards measures against COVID-19	Negative
		Ambivalent
		Positive
3.	Media repertoires	Traditional media (print, broadcasting)
		Online legacy (newspapers or public broadcasters)
		Social media
4	Messenger use
5	Experiences with misinformation	None
		Experience but no concrete incident
		Concrete experiences
6	Contact point with misinformation	Legacy news media
		Social media
		Instant messengers (direct)
		Instant messengers (group)
		Face to face
7	Personal response to misinformation	Ignoring
		Direct countering
		Indirect countering
		Avoidance of contact
8	Circumstances for different responses	Personal contact
		Close others
		Distant others
9	Attitudes towards countermeasures on public platforms	Negative
		Ambivalent
		Positive
10	Attitudes towards countermeasures on instant messengers	Negative
		Ambivalent
		Positive
11	Tackles social bots on instant messengers

Notes. Categories 2–9 are not part of the analyses for this paper but were analyzed for the student research project that collected the data. Category 11 was used to identify relevant paragraphs within users’ considerations of fact bots as counter measures on instant messengers.