Credibility at stake. A comparative analysis of different hate speech comments on journalistic credibility and support on climate protection measures

Figures & data

Table 1. Sample (Frequency, Percent, Population Quota in Percent).

Gender^1
Female	262	53.9	50.2*
Male	224	46.1	49.8*
Age
<30 Years	127	26.1	20.9*
30 to 39 Years	113	23.3	20.0*
40 to 49 Years	101	20.8	19.2*
50 to 64 Years	51	10.5	22.8*
65+ Years	94	19.3	17.1*
Highest formal education
Primary education	47	9.7	17.5**
Lower secondary school education (e.g. apprenticeship)	149	30.7	33.0**
Secondary technical school education (e.g. BMS)	131	27	30.4**
A Level (e.g. AHS-/BHS-Matura)	71	14.6
University education	88	18.1	19.1**
Political orientation
Left	100	20.6
Centre	276	56.8
Right	110	22.6
Voting Intention
Right-wing	138	30.3	29***
others	293	64.3	65***
Non-voters	25	5.5
Online News Usage
Several Times daily/daily	250	51.5
Several times the week	97	20
Once a week/ Less than once a week	93	19.2
Never	48	9.5
N	486

Note. Mean survey duration 8.27 minutes, 1 = 4 options: ‘female’, ‘male’, ‘other, namely’ and ‘I do not wish to provide any information’. *Reference data from Eurostat database; **Statistik Austria (16.05.2023): https://www.statistik.at/statistiken/bevoelkerung-und-soziales/bildung/bildung-in-zahlen; ***INSA (07.09.2023): https://politpro.eu/de/oesterreich/wahlumfragen.

Figure 1. Stimulus (Translated Version).

Source. Der Standard (10.07.2023). Letzte Generation begann am Wiener Schwedenplatz neue Protestwelle [Last generation started new wave of protests at Schwedenplatz in Vienna]. https://www.derstandard.at/story/3000000178190/letzte-generation-protestiert-am-schwedenplatz-in-w.

Table 2. Descriptive Statistics (Means).

	TG1	TG2	TG3	TG4	TG5	TG6	CG	m	H-Test
Credibility Index	4.89	4.81	4.71	4.89	4.61	4.45	4.98	4.74	.15
CP Personally	3.07	3.07	3.07	2.89	3.09	3.13	2.91	3.04	.49
CP Measures	3.33	3.37	3.31	3.3	3.36	3.48	3.41	3.36	.96
CP Demonstrations	2.07	2.02	1.58	1.88	1.81	1.91	1.83	1.87	.13
Non-appropriate Language	2.0	2.14	2.45	2.7	2.82	3.08	___	2.53	.00***
Hate speech	2.59	2.6	2.79	3.28	3.0	3.58	___	3.09	.00***
N	70	76	75	81	76	76	32	486

Note. Credibility Index measured by 4 items on 7-point scale from bad to very good; Climate Protection personally measured on 4-point scale from unimportant to very important; Support Climate Protection Measures, measured by 6 items on a 5-point scale: 1 = completely disagree, 5 = completely agree; Climate Protection demonstrations Index measured by 3 items on 4-point scale from not at all true to absolutely true; Non-appropriate Language; Hate speech: 1 = completely disagree, 4 = completely agree; +p < .10, *p < .05, **p < .01, ***p < .001.

Table 3. Regression models I and II.

	I DV: Credibility	II DV: support CP measures
(Constant)	4.1 (.57)***	1.24 (.34)***
Gender	−.10 (.13)	.09 (.08)
Age	.00 (.01)	−.00 (.03)
Education	−.06 (.05)	−.10 (.03)***
Political Interest	.07 (.09)	−.11 (.05)*
Efficacy	________	.09 (.06)
Voting Intention	−.28 (.16)+	−.36 (.09)***
Credibility	________	.06 (.03)*
CP Personally	________	.47 (.05)***
CP Measures	.30 (.09)***	________
CP Demonstrations	.07 (.07)	.186 (.04)***
Non-appropriate Language	−.07 (.06)	.09 (.03)**
News Media Usage	−.03 (.04)	−.02 (.02)
R^2	.114 486	.543 486
N

Note. Beta (SD). Gender: 0 = female, 1 = male; Age ascending; Education: 1 = max. primary education, 5 = university education; Political interest (1 = not at all, 4 = very interested); Voting Intention: 1=(ÖVP, SPÖ, NEOS, Die Grünen), 2 = FPÖ; Efficacy: 1 = low, 4 = high; Credibility of the journalistic article: 1 = bad, 7 = very good; Climate Protection Personally: 1 = not important, 4 = very important; Support climate protection measures: 1 = completely disagree, 5 = completely agree; Support climate protection demonstration, measured by 3 items: 1 = not true at all, 5 = is absolutely true; News Media Usage: 1 = never, 6 = several times daily, +p < .10, *p < .05, **p < .01, ***p < .001.

Table A1. Stimulus Hate speech comments (According to the Intensity scale of Bahador, 2023).

	TG1: Disagreement	TG2: Negative actions	TG3: Negative character	TG4: Demonising & Dehumanising	TG5: Violence	TG6: Death
Characteristics	Responses include challenging claims, or trying to change their view.	Rhetoric includes negative non-violent actions associated with the group.	Rhetoric includes non-violent characterisations and insults.	Rhetoric includes sub-human and superhuman characteristics.	Responses include calls for literal violence/metaphoric aspirational phy-sical harm or death.	Responses include the literal death/elimination of a group.
Example	False, incorrect, challenge, persuade, change minds	Threatened, Stole, outrageous act, poor treatment	Stupid, Thief, aggressor, Fake, crazy	Rat, monkey, Nazi, Demon, cancer, monster	Punched, raped, starved, Torturing, mugging	Killed, annihilate, destroy
Stimulus in Experiment / Source	Ich bin gegen diese sinnlosen Klimakleber Aktionen. die rein gar nichts bringen und völlig an der Sache vorbei gehen.	Wahnsinn. diese ‘Klimaaktivisten’ fliegen alle nach Bali und sonst wo hin und hier blockieren Sie die Straßen der ehrlichen Arbeiter!	Diagnose ausgeprägter Narzissmus. Hinzu kommt inhaltsleeres in sich widersprüch-liches Geschwafel. Prognose ihr seid nicht normal!	Diese Klimaaktivisten sind ein tödliches Krebsgeschwür und zerstört unsere Gesellschaft.	Warum darf man da nicht zur Selbsthilfe greifen - und diesen Leuten einfach eine reinhauen?!	Es wird Zeit diese Klimaterroristen alle zu überfahren. Vergasen ist auch eine Lösung!
Translation	I am against these pointless climate sticker campaigns that achieve absolutely nothing and completely miss the point.	Madness. these ‘climate activists’ all fly to Bali and elsewhere and here you block the roads of honest workers!	Diagnosis of pronounced narcissism. In addition, there is empty contradictory gibberish. Prognosis you are not normal!	These climate activists are a deadly cancer and are destroying our society.	Why can’t we help ourselves and just punch these people in the face?	It’s time to run over all these climate terrorists. Gassing is also a solution!

Table A2. Regression Models on Article Credibility.

	TG1	TG2	TG3	TG4	TG5	TG6	CG
(Constant)	4.92 (1.2) ***	4.63 (1.3)***	4.57 (1.7)**	2.2 (1.5)	3.94 (1.4)**	4.16 (.16)*	−.32 (2.1)
Gender	−.12 (.36)	−.48 (.29)	−.02 (.41)	.06 (.3)	.46 (.34)	−.23 (.34)	.38 (.52)
Age	−.02 (.01)+	.03 (.01)**	.02 (.02)	.01 (.01)	.00 (.01)	.01 (.01)	.03 (.02)
Education	−.1 (.14)	−.08 (.12)	.05 (.16)	.06 (.11)	−.07 (.13)	−.12 (.15)	−.06 (.24)
Political Interest	.09 (.25)	.27 (.19)	−.11 (.28)	−.05 (.21)	−.14 (.25)	−.15 (.25)	.24 (.29)
Voting Intention	−.07 (.45)	−.06 (.32)	−.92 (.47)+	.15 (.43)	−.78 (.44)+	.13 (.43)	.42 (.49)
CP Measures	.51 (.2)*	−.18 (.21)	.21 (.25)	.64 (.22)**	.18 (.19)	.24 (.24)	.59 (.42)
CP Demonstrations	.09 (.19)	.24 (.13)+	.32 (.31)	−.11 (.16)	.13 (.17)	−.00 (.19)	−.00 (.28)
Non-appropriate Language	−.4 (.17)*	−.29 (.14)*	−.27 (.2)	.15 (.32)	.09 (.16)	.22 (.16)	____
News Media Usage	−.07 (.11)	−.01(.1)	−.02(.13)	.04 (.11)	.18 (.11)	−.23 (.12)+	−.02 (.19)
R^2	.32	.29	.23	.26	.28	.17	.31
n	70	76	75	81	76	76	32

Note. Beta values (SD). DV: Credibility of the Journalistic article, measured by 4 items: 1 = bad, 7 = very good. IV: Gender: 0 = female, 1 = male; Education: 1 = max. primary education, 5 = university education; Age ascending; Voting Intention: 1=(ÖVP, SPÖ, NEOS, Die Grünen), 2 = FPÖ; Efficacy, measured by 4 items: 1 = low, 5 = high; Political interest (1 = not at all, 4 = very interest); Political ideology: 1 = left, 10 = right; Climate Protection Personally: 1 = not important, 4 = very important; Support Climate Protection Measures, measured by 6 items: 1 = completely disagree, 5 = completely agree; Support climate protection demonstration, measured by 3 items: 1 = not true at all, 5 = is absolutely true; Non-appropriate Language: 1 = completely disagree, 4 = completely agree; News Media Usage: 1 = never, 6 = several times daily; +p <.10, *p <.05, **p<.01, ***p<.001.

Table A3. Regression models on support climate protection measures.

	TG1	TG2	TG3	TG4	TG5	TG6	CG
(Constant)	.17 (1.0)	1.96 (.79)*	.36 (.87)	2.5 (.85)**	1.02 (.99)	1.63 (1.03)	1.49 (1.2)
Gender	.01 (.24)	.19 (.18)	−.11 (.20)	.08 (.17)	.29 (.22)	−.09 (.22)	−.10 (.29)
Age	.01 (.01)	.00 (.01)	−.00 (.01)	.01 (.01)	−.01 (.01)	.00 (.01)	−.02 (.01)
Education	−.00 (.09)	.13 (.07)+	.12 (.07)	.08 (.06)	.18 (.08)*	.10 (.09)	.23 (.12)+
Political Interest	.27 (.17)	−.13 (.12)	−.23 (.13)+	.01 (.15)	−.11 (.16)	−.06 (.15)	.20 (.16)
Efficacy	−.08 (.17)	.09 (.14)	.20 (.15)	−.20 (.15)	−.17 (.22)	.26 (.17)	−.17 (.17)
Voting Intention	−.03 (.29)	−.25 (.19)	.04 (.24)	−.98 (.24)***	−.27 (.29)	−.36 (.25)	−.36 (.3)
Credibility	.22 (.09)*	−.19 (.09)*	.02 (.07)	.13 (.08)+	.12 (.09)	.07 (.08)	.21 (.13)
CP Personally	.36 (.16)*	.64 (.13)***	.71 (.12)***	.32 (.11)**	.63 (.15)***	.22 (.15)	.14 (.2)
CP Demonstrations	.15 (.13)	.15 (.08)+	.26 (.14)+	.11 (.09)	.1 (.12)	.27 (.11)*	.35 (.15)*
Non-appropriate Language	.19 (.11)+	−.04 (.09)	.14 (.09)	.07 (.09)	.07 (.1)	.07 (.1)	____
News Media Usage	−.04 (.07)	−.03 (.06)	−.02 (.06)	.02 (.06)	−.06 (.07)	−.05 (.07)	.11 (.11)
R^2	.54	.60	.69	.69	.61	.54	.73
n	70	76	75	81	76	76	32

Note. Beta Values (SD). DV: Support Measures, measured by 6 items: 1 = completely disagree, 5 = completely agree. IV: Gender: 0 = female, 1 = male; Education: 1 = max. primary education, 5 = university education; Age ascending; Political interest (1 = not at all, 4 = very interest); Efficacy, measured by 4 items: 1 = low, 5 = high; Voting Intention: 1=(ÖVP, SPÖ, NEOS, Die Grünen), 2 = FPÖ; Credibility of the journalistic article, measured by 4 items: 1 = bad, 7 = very good; Climate Protection Personally: 1 = not important, 4 = very important; Support demonstration, measured by 3 items: 1 = not true at all, 5 = is absolutely true; +p <.10, *p <.05, **p<.01, ***p<.001.

Bahador, B. (2023). Monitoring hate speech and the limits of current definition. In C. Strippel, S. Paasch-Colberg, M. Emmer, & J. Trebbe (Eds.), Challenges and perspectives of hate speech research (pp. 291–286). https://doi.org/10.48541/dcr.v12.17

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Data availability statement

The data that support the findings of this study are openly available in OSF at https://osf.io/evt9r/