This experiment investigates how individuals’ meta-knowledge (the self-perception of one’s knowledge) influences selective exposure to and elaboration of information about climate change with climate change self-schema as possible mediator. Participants’ (N = 510) meta-knowledge was manipulated by receiving fake feedback after a climate change knowledge test. There were no group differences in selective exposure and selective elaboration. Correlational evidence tentatively speaks for a “rich-get-richer” process of information selection and elaboration. This could be explained through climate change self-schemas which differed significantly between conditions (d = 0.26) and correlated positively with selective exposure (r = .36) and elaboration (r = .28).
AllgoodS.WalstadW. B. (2016). The effects of perceived and actual financial literacy on financial behaviors. Economic Inquiry, 54(1), 675–697. https://doi.org/10.1111/ecin.12255
BauerM. W. (2008). Survey research and the public understanding of science. In BucchiM.TrenchB. (Eds.), Handbook of public communication of science and technology (pp. 125–144). Routledge.
4.
BergerI. E.RatchfordB. T.HainesG. H. (1994). Subjective product knowledge as a moderator of the relationship between attitudes and purchase intentions for a durable product. Journal of Economic Psychology, 15(2), 301–314. https://doi.org/10.1016/0167-4870(94)90006-X
5.
BrossardD.LewensteinB. V. (2009). A critical appraisal of models of public understanding of science: Using practice to inform theory. In KahlorL.StoutP. (Eds.), Communicating science (pp. 25–53). Routledge.
6.
CargninoM.NeubaumG.WinterS. (2023). We’re a good match: Selective political friending on social networking sites. Communications, 48(2), 202–225. https://doi.org/10.1515/commun-2021-0028
7.
CarlsonJ. P.VincentL. H.HardestyD. M.BeardenW. O. (2009). Objective and subjective knowledge relationships: A quantitative analysis of consumer research findings. Journal of Consumer Research, 35(5), 864–876. https://doi.org/10.1086/593688
8.
ClaytonS. (2003). Environmental identity: A conceptual and an operational definition. In ClaytonS.OpotowS. (Eds.), Identity and the natural environment: The psychological significance of nature (pp. 45–65). MIT Press.
9.
DunloskyJ.RawsonK. A. (2012). Overconfidence produces underachievement: Inaccurate self evaluations undermine students’ learning and retention. Learning and Instruction, 22(4), 271–280. https://doi.org/10.1016/j.learninstruc.2011.08.003
10.
DunningD. (2011). Chapter five—the Dunning–Kruger effect: On being ignorant of one’s own ignorance. In OlsonJ. M.ZannaM. P. (Eds.), Advances in experimental social psychology (Vol. 44, pp. 247–296). Elsevier. https://doi.org/10.1016/B978-0-12-385522-0.00005-6
11.
EllenP. S. (1994). Do we know what we need to know? Objective and subjective knowledge effects on pro-ecological behaviors. Journal of Business Research, 30(1), 43–52. https://doi.org/10.1016/0148-2963(94)90067-1
12.
EvelandW. P.Jr. (2001). The cognitive mediation model of learning from the news: Evidence from nonelection, off-year election, and presidential election contexts. Communication Research, 28(5), 571–601.
13.
FeldmanL.HartP. S. (2016). Using political efficacy messages to increase climate activism: The mediating role of emotions. Science Communication, 38(1), 99–127. https://doi.org/10.1177/1075547015617941
14.
FeldmanL.HartP. S. (2018). Broadening exposure to climate change news? How framing and political orientation interact to influence selective exposure. Journal of Communication, 68(3), 503–524. https://doi.org/10.1093/joc/jqy011
15.
FischerH.AmelungD.SaidN. (2019). The accuracy of German citizens’ confidence in their climate change knowledge. Nature Climate Change, 9(10), 776–780. https://doi.org/10.1038/s41558-019-0563-0
16.
FischerH.SaidN. (2021). Importance of domain-specific metacognition for explaining beliefs about politicized science: The case of climate change. Cognition, 208, 104545. https://doi.org/10.1016/j.cognition.2020.104545
17.
FrauhammerL. T.NeubaumG. (2023). Metacognitive effects of attitudinal (in)congruence on social media: Relating processing fluency, subjective knowledge, and political participation. Frontiers in Psychology, 14, Article 1146674. https://doi.org/10.3389/fpsyg.2023.1146674
18.
FrühW.SchönbachK. (1982). Der dynamisch-transaktionale Ansatz. Ein neues Paradigma der Medienwirkungen [The dynamic-transactional approach. A new paradigm of media effects]. Publizistik, 27, 74–88.
19.
GriffinR. J.DunwoodyS.NeuwirthK. (1999). Proposed model of the relationship of risk information seeking and processing to the development of preventive behaviors. Environmental Research Section A, 80, 230–245.
20.
GuyS.KashimaY.WalkerI.O’NeillS. (2014). Investigating the effects of knowledge and ideology on climate change beliefs: Knowledge, ideology, and climate change beliefs. European Journal of Social Psychology, 44(5), 421–429. https://doi.org/10.1002/ejsp.2039
21.
HadarL.SoodS.FoxC. R. (2013). Subjective knowledge in consumer financial decisions. Journal of Marketing Research, 50(3), 303–316. https://doi.org/10.1509/jmr.10.0518
22.
HoS. S.YangX.ThanwaraniA.ChanJ. M. (2017). Examining public acquisition of science knowledge from social media in Singapore: An extension of the cognitive mediation model. Asian Journal of Communication, 27(2), 193–212.
23.
HolbrookA. L.BerentM. K.KrosnickJ. A.VisserP. S.BoningerD. S. (2005). Attitude importance and the accumulation of attitude-relevant knowledge in memory. Journal of Personality and Social Psychology, 88(5), 749–769. https://doi.org/10.1037/0022-3514.88.5.749
24.
JangS. M. (2014). Seeking congruency or incongruency online? Examining selective exposure to four controversial science issues. Science Communication, 36(2), 143–167. https://doi.org/10.1177/1075547013502733
25.
KahlorL.DunwoodyS.GriffinR. J.NeuwirthK. (2006). Seeking and processing information about impersonal risk. Science Communication, 28(2), 163–194. https://doi.org/10.1177/1075547006293916
26.
KahlorL. A. (2007). An augmented risk information seeking model: The case of global warming. Media Psychology, 10(3), 414–435. https://doi.org/10.1080/15213260701532971
27.
KatzE.BlumlerJ. G.GurevitchM. (1973). Uses and gratifications research. The Public Opinion Quarterly, 37(4), 509–523. https://doi.org/10.1086/268109
28.
KnoblochS.CarpentierF. D.ZillmannD. (2003). Effects of salience dimensions of informational utility on selective exposure to online news. Journalism & Mass Communication Quarterly, 80(1), 91–108. https://doi.org/10.1177/10776990030800010
29.
Knobloch-WesterwickS. (2014). Choice and preference in media use: Advances in selective exposure theory and research. Routledge. https://doi.org/10.4324/9781315771359
30.
Knobloch-WesterwickS. (2015). The selective exposure self- and affect-management (SESAM) model: Applications in the realms of race, politics, and health. Communication Research, 42(7), 959–985. https://doi.org/10.1177/0093650214539173
31.
Knobloch-WesterwickS.MothesC.PolavinN. (2020). Confirmation bias, ingroup bias, and negativity bias in selective exposure to political information. Communication Research, 47(1), 104–124. https://doi.org/10.1177/0093650217719596
32.
KrieglsteinF.BeegeM.ReyG. D.Sanchez-StockhammerC.SchneiderS. (2023). Development and validation of a theory-based questionnaire to measure different types of cognitive load. Educational Psychology Review, 35(1), 9. https://doi.org/10.1007/s10648-023-09738-0
LeeS.DiehlT.ValenzuelaS. (2021). Rethinking the virtuous circle hypothesis on social media: Subjective versus objective knowledge and political participation. Human Communication Research, 48(1), 57–87. https://doi.org/10.1093/hcr/hqab014
35.
LiederF.PlunkettD.HamrickJ. B.RussellS. J.HayN.GriffithsT. (2014). Algorithm selection by rational metareasoning as a model of human strategy selection [Conference session]. Advances in Neural Information Processing Systems, Montreal, Quebec, Canada (Volume 27). https://doi.org/10.13140/2.1.2563.1686
36.
MarkusH. (1999). Self-schemata and processing information about the self. Journal of Personality and Social Psychology, 35(2). https://doi.org/10.1037/0022-3514.35.2.63
MishraS. K.KumarM. (2011). How mutual fund investors’ objective and subjective knowledge impacts their information search and processing behaviour. Journal of Financial Services Marketing, 16(1), 27–41. https://doi.org/10.1057/fsm.2011.1
39.
MoormanC.DiehlK.BrinbergD.KidwellB. (2004). Subjective knowledge, search locations, and consumer choice. Journal of Consumer Research, 31(3), 673–680. https://doi.org/10.1086/425102
40.
NelsonT. O.NarensL. (1990). Metamemory: A theoretical framework and new findings. In BowerG. H. (Ed.), Psychology of learning and motivation (Vol. 26, pp. 125–173). Elsevier. https://doi.org/10.1016/S0079-7421(08)60053-5
41.
NisbetM. C. (2009). Framing science: A new paradigm in public engagement. In KahlorL.StoutP. (Eds.), Communicating science (pp. 54–81). Routledge.
42.
NisbetM. C.ScheufeleD. A. (2009). What’s next for science communication? Promising directions and lingering distractions. American Journal of Botany, 96(10), 1767–1778. https://doi.org/10.3732/ajb.0900041
43.
OnelN.MukherjeeA. (2016). Consumer knowledge in pro-environmental behavior: An exploration of its antecedents and consequences. World Journal of Science, Technology and Sustainable Development, 13(4), 328–352. https://doi.org/10.1108/WJSTSD-01-2016-0004
44.
SaidN.FrauhammerL. T.HuffM. (2023). Consensus messaging in climate change communication: Metacognition as moderator variable in the gateway belief model. Journal of Environmental Psychology, 9, 102128. https://doi.org/10.1016/j.jenvp.2023.102128
SchäferS. (2020). Illusion of knowledge through Facebook news? Effects of snack news in a news feed on perceived knowledge, attitude strength, and willingness for discussions. Computers in Human Behavior, 103, 1–12. https://doi.org/10.1016/j.chb.2019.08.031
47.
SchmittJ. B.SchneiderF. M.WeinmannC.RothF. S. (2019). Saving tiger, orangutan & co: How subjective knowledge and text complexity influence online information seeking and behavior. Information, Communication & Society, 22(9), 1193–1211. https://doi.org/10.1080/1369118X.2017.1410206
48.
SchneiderF. M.WeinmannC.RothF. S.KnopK.VordererP. (2016). Learning from entertaining online video clips? Enjoyment and appreciation and their differential relationships with knowledge and behavioral intentions. Computers in Human Behavior, 54, 475–482. https://doi.org/10.1016/j.chb.2015.08.028
ShenhavA.MusslickS.LiederF.KoolW.GriffithsT. L.CohenJ. D.BotvinickM. M. (2017). Toward a rational and mechanistic account of mental effort. Annual Review of Neuroscience, 40(1), 99–124. https://doi.org/10.1146/annurev-neuro-072116-031526
51.
ShulmanH. C.DixonG. N.BullockO. M.Colón AmillD. (2020). The effects of jargon on processing fluency, self-perceptions, and scientific engagement. Journal of Language and Social Psychology, 39(5–6), 579–597. https://doi.org/10.1177/0261927X20902177
52.
StoutenboroughJ. W.VedlitzA. (2014). The effect of perceived and assessed knowledge of climate change on public policy concerns: An empirical comparison. Environmental Science & Policy, 37, 23–33. https://doi.org/10.1016/j.envsci.2013.08.002
53.
SuldovskyB. (2017). The information deficit model and climate change communication. In von StorchH. (Ed.), Oxford research encyclopedia of climate science. Oxford University Press. https://doi.org/10.1093/acrefore/9780190228620.013.301
TewksburyD. (2003). What do Americans really want to know? Tracking the behavior of news readers on the internet. Journal of Communication, 53(4), 694–710. https://doi.org/10.1111/j.1460-2466.2003.tb02918.x
56.
ThallerA.BrudermannT. (2020). “You know nothing, John Doe”–Judgmental overconfidence in lay climate knowledge. Journal of Environmental Psychology, 69, 101427. https://doi.org/10.1016/j.jenvp.2020.101427
57.
WallaceL. E.PattonK. M.LuttrellA.SawickiV.FabrigarL. R.TeenyJ.MacDonaldT. K.PettyR. E.WegenerD. T. (2020). Perceived knowledge moderates the relation between subjective ambivalence and the “impact” of attitudes: An attitude strength perspective. Personality and Social Psychology Bulletin, 46(5), 709–722. https://doi.org/10.1177/0146167219873492
58.
WesterwickA.JohnsonB. K.Knobloch-WesterwickS. (2017). Change your ways: Fostering health attitudes toward change through selective exposure to online health messages. Health Communication, 32(5), 639–649. https://doi.org/10.1080/10410236.2016.1160319
59.
YangZ. J.AloeA. M.FeeleyT. H. (2014). Risk information seeking and processing model: A meta-analysis. Journal of Communication, 64(1), 20–41. https://doi.org/10.1111/jcom.12071
60.
YangZ. J.SeoM.RickardL. N.HarrisonT. M. (2015). Information sufficiency and attribution of responsibility: Predicting support for climate change policy and pro-environmental behavior. Journal of Risk Research, 18(6), 727–746. https://doi.org/10.1080/13669877.2014.910692
61.
ZhaoX. (2009). Media use and global warming perceptions: A snapshot of the reinforcing spirals. Communication Research, 36(5), 698–723. https://doi.org/10.1177/0093650209338911
62.
ZillmannD.BryantJ. (Eds.) (1985). Selective exposure to communication. Routledge.
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