Clark, A. (2016). Surfing uncertainty: Prediction, action, and the embodied mind. Oxford University Press.
Druckman, J. N., & McGrath, M. C. (2019). The evidence for motivated reasoning in climate change preference formation. Nature Climate Change, 9(2), 111–119. https://doi.org/10.1038/s41558-018-0360-1
Gerber, A., & Green, D. (1999). Misperceptions about perceptual bias. Annual Review of Political Science, 2(1), 189–210. https://doi.org/10.1146/annurev.polisci.2.1.189
Hohwy, J. (2013). The predictive mind (First edition). Oxford University Press.
Tappin, B. M., & Gadsby, S. (2019). Biased belief in the Bayesian brain: A deeper look at the evidence. Consciousness and Cognition, 68(2019), 107–114. https://doi.org/10.1016/j.concog.2019.01.006
“Bayesian Brain” (e.g., Clark, 2016; Hohwy, 2013)
\(\forall M \in \mathbb{M}, \quad P(M | D)=
\frac{P(D|M)}{P(D)} P(M)\)
Not necessarily incompatible with “Bayesian Thinking” (Gerber & Green, 1999; Druckman & McGrath, 2019; Tappin & Gadsby, 2019)
Druckman, J. N., & McGrath, M. C. (2019). The evidence for motivated reasoning in climate change preference formation. Nature Climate Change, 9(2), 111–119. https://doi.org/10.1038/s41558-018-0360-1
“The distinction in the process matters because in the directionally motivated case, opinion change would require altering the individual’s motivations (or satisfying their goals . . .), whereas in the accuracy-motivated case it would require meeting (or altering) their standards of credibility.”
Bail, C. A., Argyle, L. P., Brown, T. W., Bumpus, J. P., Chen, H., Hunzaker, M. B. F., Lee, J., Mann, M., Merhout, F., & Volfovsky, A. (2018). Exposure to opposing views on social media can increase political polarization. Proceedings of the National Academy of Sciences, 115(37), 9216–9221. https://doi.org/10.1073/pnas.1804840115
Kahan, D. M., Braman, D., Cohen, G. L., Gastil, J., & Slovic, P. (2010). Who fears the HPV vaccine, who doesn’t, and why? An experimental study of the mechanisms of cultural cognition. Law and Human Behavior, 34(6), 501–516. https://doi.org/10.1007/s10979-009-9201-0
Lu, Y., & Myrick, J. G. (2016). Cross-cutting exposure on Facebook and political participation: Unraveling the effects of emotional responses and online incivility. Journal of Media Psychology, 28(3), 100–110. https://doi.org/10.1027/1864-1105/a000203
Metzger, M. J., Hartsell, E. H., & Flanagin, A. J. (2020). Cognitive dissonance or credibility? A comparison of two theoretical explanations for selective exposure to partisan news. Communication Research, 47(1), 3–28. https://doi.org/10.1177/0093650215613136
Mutz, D. C. (2002). Cross-cutting social networks: Testing democratic theory in practice. The American Political Science Review, 96(1), 111–126. https://www.jstor.org/stable/3117813
Mutz, D. C., & Martin, P. S. (2001). Facilitating communication across lines of political difference: The role of mass media. American Political Science Review, 95(1), 97–114. https://doi.org/10.1017/S0003055401000223
Stroud, N. J. (2010). Polarization and partisan selective exposure. Journal of Communication, 60(3), 556–576. https://doi.org/10.1111/j.1460-2466.2010.01497.x
Suhay, E., & Erisen, C. (2018). The role of anger in the biased assimilation of political information. Political Psychology, 39(4), 793–810. https://doi.org/10.1111/pops.12463
Taber, C. S., & Lodge, M. (2006). Motivated skepticism in the evaluation of political beliefs. American Journal of Political Science, 50(3), 755–769. https://doi.org/10.1111/j.1540-5907.2006.00214.x
Exposure to dissonant views through mass media (Mutz, 2002; Mutz & Martin, 2001)
Itti, L., & Baldi, P. (2009). Bayesian surprise attracts human attention. Vision Research, 49(10), 1295–1306. https://doi.org/10.1016/j.visres.2008.09.007
Noordewier, M. K., Topolinski, S., & Van Dijk, E. (2016). The temporal dynamics of surprise. Social and Personality Psychology Compass, 10(3), 136–149. https://doi.org/10.1111/spc3.12242
Vogl, E., Pekrun, R., Murayama, K., Loderer, K., & Schubert, S. (2019). Surprise, curiosity, and confusion promote knowledge exploration: Evidence for robust effects of epistemic emotions. Frontiers in Psychology, 10, Article 2474. https://doi.org/10.3389/fpsyg.2019.02474
Vogl, E., Pekrun, R., Murayama, K., & Loderer, K. (2020). Surprised–curious–confused: Epistemic emotions and knowledge exploration. Emotion, 20(4), 625–641. https://doi.org/10.1037/emo0000578
Surprise
Difference between prior \(S(D, \mathbb{M})
= KL(P(M|D), P(M)) = \int_\mathbb{M} P(M|D) \log
\frac{P(M|D)}{P(M)}dM\)
and posterior belief (Itti &
Baldi, 2009)
Initial reaction to an unexpected event (Noordewier et al., 2016)
High-Confidence-Errors
(Vogl et al., 2019,
2020)
Dietrich, F., Kugler, T., Hennings, S., Conrad, C., Schneider, F. M., & Vorderer, P. (2022, May 26–30). The role of epistemic emotions and empathy in eudaimonic entertainment experiences and political news processing. Paper accepted for presentation at the 72nd Conference of the International Communication Association (ICA), Paris, France.
D’Mello, S., & Graesser, A. (2012). Dynamics of affective states during complex learning. Learning and Instruction, 22(2), 145–157. https://doi.org/10.1016/j.learninstruc.2011.10.001
Kang, M. J., Hsu, M., Krajbich, I. M., Loewenstein, G., McClure, S. M., Wang, J. T., & Camerer, C. F. (2009). The wick in the candle of learning: Epistemic curiosity activates reward circuitry and enhances memory. Psychological Science, 20(8), 963–973. https://doi.org/10.1111/j.1467-9280.2009.02402.x
Muis, K. R., Pekrun, R., Sinatra, G. M., Azevedo, R., Trevors, G., Meier, E., & Heddy, B. C. (2015). The curious case of climate change: Testing a theoretical model of epistemic beliefs, epistemic emotions, and complex learning. Learning and Instruction, 39, 168–183. https://doi.org/10.1016/j.learninstruc.2015.06.003
Trevors, G. J., Muis, K. R., Pekrun, R., Sinatra, G. M., & Winne, P. H. (2016). Identity and epistemic emotions during knowledge revision: A potential account for the backfire effect. Discourse Processes, 53(5-6), 339–370. https://doi.org/10.1080/0163853X.2015.1136507
Vogl, E., Pekrun, R., Murayama, K., Loderer, K., & Schubert, S. (2019). Surprise, curiosity, and confusion promote knowledge exploration: Evidence for robust effects of epistemic emotions. Frontiers in Psychology, 10, Article 2474. https://doi.org/10.3389/fpsyg.2019.02474
Vogl, E., Pekrun, R., Murayama, K., & Loderer, K. (2020). Surprised–curious–confused: Epistemic emotions and knowledge exploration. Emotion, 20(4), 625–641. https://doi.org/10.1037/emo0000578
Epistemic Emotions
RQ1: What is the effect of cross-cutting exposure on recipients’ experience of epistemic emotions (cross-cutting exposure → epistemic emotions)?
RQ2: What is the mediating role of epistemic emotions experienced while reading a political news article on recipients’ posterior opinion about the topic of the news article (crosscutting exposure → epistemic emotions → posterior opinion)?
Bochner, S., & Insko, C. A. (1966). Communicator discrepancy, source credibility, and opinion change. Journal of Personality and Social Psychology, 4(6), 614–621. https://doi.org/10.1037/h0021192
Briñol, P., Petty, R. E., & Tormala, Z. L. (2004). Self-validation of cognitive responses to advertisements. Journal of Consumer Research, 30(4), 559–573. https://doi.org/10.1086/380289
Chaiken, S., & Maheswaran, D. (1994). Heuristic processing can bias systematic processing: Effects of source credibility, argument ambiguity, and task importance on attitude judgment. Journal of Personality and Social Psychology, 66(3), 460–473. https://doi.org/10.1037/0022-3514.66.3.460
Hovland, C. I., Janis, I. L., & Kelley, H. H. (1953). Communication and persuasion. Yale University Press.
Pornpitakpan, C. (2004). The persuasiveness of source credibility: A critical review of five decades’ evidence. Journal of Applied Social Psychology, 34(2), 243–281. https://doi.org/10.1111/j.1559-1816.2004.tb02547.x
Trustworthiness and expertise (Hovland et al., 1953; Pornpitakpan, 2004)
Attitude change only when perceived credibility is high (Bochner
& Insko, 1966; Briñol et al., 2004)
e.g., based on
credibility heuristics (Chaiken & Maheswaran, 1994)
RQ3: What is the effect of cross-cutting exposure on recipients’ experience of epistemic emotions if perceived source credibility is manipulated to be high or low (cross-cutting exposure with high/low credibility → epistemic emotions)?
RQ4: What is the mediating role of epistemic emotions experienced while reading a political news article on recipients’ posterior opinion about the topic represented in the news article, if perceived source credibility is manipulated to be high or low (cross-cutting exposure with high/low credibility → epistemic emotions → posterior opinion)?
Hofer, B. K., & Pintrich, P. R. (1997). The development of epistemological theories: Beliefs about knowledge and knowing and their relation to learning. Review of Educational Research, 67(1), 88–140. https://doi.org/10.3102/00346543067001088
Muis, K. R., Pekrun, R., Sinatra, G. M., Azevedo, R., Trevors, G., Meier, E., & Heddy, B. C. (2015). The curious case of climate change: Testing a theoretical model of epistemic beliefs, epistemic emotions, and complex learning. Learning and Instruction, 39, 168–183. https://doi.org/10.1016/j.learninstruc.2015.06.003
Visser, P. S., Bizer, G. Y., & Krosnick, J. A. (2006). Exploring the latent structure of strength‐related attitude attributes. In Advances in Experimental Social Psychology (Vol. 38, pp. 1–67). Academic Press. https://doi.org/10.1016/S0065-2601(06)38001-X
Visser, P. S., Krosnick, J. A., & Simmons, J. P. (2003). Distinguishing the cognitive and behavioral consequences of attitude importance and certainty: A new approach to testing the common-factor hypothesis. Journal of Experimental Social Psychology, 39(2), 118–141. https://doi.org/10.1016/S0022-1031(02)00522-X
Vogl, E., Pekrun, R., Murayama, K., Loderer, K., & Schubert, S. (2019). Surprise, curiosity, and confusion promote knowledge exploration: Evidence for robust effects of epistemic emotions. Frontiers in Psychology, 10, Article 2474. https://doi.org/10.3389/fpsyg.2019.02474
Vogl, E., Pekrun, R., Murayama, K., & Loderer, K. (2020). Surprised–curious–confused: Epistemic emotions and knowledge exploration. Emotion, 20(4), 625–641. https://doi.org/10.1037/emo0000578
High confidence errors (Vogl et al., 2019, 2020) vs. defense mechanisms (Visser et al., 2003, 2006)
Epistemic beliefs (e.g., certainty of knowledge) associated with intensity of epistemic emotions (Hofer & Pintrich, 1997; Muis et al., 2015)
H4: The effect of cross-cutting exposure on recipients’ experience of epistemic emotions will be moderated by (a) recipients’ confidence in their prior opinion and (b) recipients’ epistemic beliefs about the certainty of knowledge.
Schneider, F. M., & Weinmann, C. (2021). In need of the devil’s advocate? The impact of cross-cutting exposure on political discussion. Political Behavior. Advance online publication. https://doi.org/10.1007/s11109-021-09706-w
N = 330 (53% male, 46% female) in a 2 × 2 × 2 preregistered online experiment (05-21 June 2021)
Age: 17–66 years (M = 21.2, SD = 10.9)
Education: overall high
Quasi experimental index for cross-cuttingness
CCLM = Opinion1 * Direction (from –2 bis +2, cf. Schneider & Weinmann, 2021)
Polarization = Opionion2 * Direction – CCLM (from –4 bis +4)
Preacher, K. J., & Selig, J. P. (2012). Advantages of Monte Carlo confidence intervals for indirect effects. Communication Methods and Measures, 6(2), 77–98. https://doi.org/10.1080/19312458.2012.679848
Manipulation Check
Only the direction of arguments had an effect on the rating of the author’s position, \(\scriptsize F(1, 326) = 1837.67, p < .001, \eta_G^2 = 0.849\), but neither had the topic, \(\scriptsize F(1, 326) = 1.221, p = .270, \eta_G^2 = .004\), nor the Topic × Direction interaction, \(\scriptsize F(1, 326) = 0.588, p = .444, \eta_G^2 = .002\)
Hypothesis Testing
Structural Equation Model, \(\scriptsize \chi^2_{robust} = 299.42, df = 183, p < .001, \chi^2/df = 1.64 CFI_{robust} = .884, RMSEA_{robust} = .044\ [90\%\ CI\ .035, .053], SRMR = .088\)
Indirect Effects: Monte Carlo simulated 95% confidence intervals (Preacher & Selig, 2012)
Druckman, J. N., & McGrath, M. C. (2019). The evidence for motivated reasoning in climate change preference formation. Nature Climate Change, 9(2), 111–119. https://doi.org/10.1038/s41558-018-0360-1
“The distinction in the process matters because in the directionally motivated case, opinion change would require altering the individual’s motivations (or satisfying their goals . . .), whereas in the accuracy-motivated case it would require meeting (or altering) their standards of credibility.”
Lodge, M., & Taber, C. S. (2013). The rationalizing voter. Cambridge University Press. https://doi.org/10.1017/CBO9781139032490
“Cold” topics
Weak surprise
Emotions as part of a rationalization process? (cf. Lodge & Taber, 2013)
Slides:
https://felix-dietrich.de/presentations/ica22/epistemic-emotions-and-cross-cutting-news
Contact:
felix.dietrich@uni-mannheim.de
Complementary Talk about Epistemic Emotions:
If
you are interested in epistemic emotions, you can also listen to my
other presentation in the same panel on the role of epistemic emotions
and empathy in eudaimonic entertainment experiences and political news
processing.