2004
Volume 46, Issue 1
  • ISSN: 1573-9775
  • E-ISSN: 2352-1236

Abstract

Abstract

There is an increasing degree of polarization in society on issues including health, climate, and immigration. Research has shown that this polarization is fueled by exposure to already accepted viewpoints, partly initiated by algorithms online. Another possible source of polarization consists of confronting people with opposing views. In response to opposing views recipients may further reinforce their initial opinion. This expectation was tested in an experiment, in which the quality of the supporting arguments in the opposing message was also manipulated. After a pretest on the basis of which two extreme standpoints were selected, subjects in the main experiment were presented with two messages, each including one of the two extreme standpoints, supported with either strong or weak arguments. There was no polarization effect – on the contrary, subjects shifted their belief in the direction of the standpoint after reading the opposing message, regardless of the argument quality. These results are compatible with other research that also shows that people shift their beliefs in relation to the content of opposing messages.

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2024-12-01
2025-02-16
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References

  1. Asker, D., & Dinas, E. (2019). Thinking fast and furious: Emotional intensity and opinion polarization in online media. Public Opinion Quarterly, 83 (3), 487-509.
    [Google Scholar]
  2. Bail, C. A., Argyle, L. P., Brown, T. W., et al. (2018). Exposure to opposing views on social media can increase political polarization. Proceedings of the National Academy of Sciences, 115 (37), 9216-9221.
    [Google Scholar]
  3. Banas, J. A., & Rains, S. A. (2010). A meta-analysis of research on inoculation theory. Communication Monographs, 77 (3), 281-311.
    [Google Scholar]
  4. Baratgin, J., & Politzer, G. (2010). Updating: A psychologically basic situation of probability revision. Thinking and Reasoning, 16 (4), 253-287.
    [Google Scholar]
  5. Bavel, J. J. van, Rathje, S., Harris, E., Robertson, C., & Sternisko, A. (2021). How social media shapes polarization. Trends in Cognitive Sciences, 25 (11), 913-916.
    [Google Scholar]
  6. Byrne, S., & Hart, P. S. (2009). The boomerang effect: A synthesis of finding and a preliminary theoretical framework. Annals of the International Communication Association, 33, 3-37.
    [Google Scholar]
  7. Carpenter, C. J. (2015). A meta-analysis of the ELM’s argument quality x processing type predictions. Human Communication Research, 41 (4), 501-534.
    [Google Scholar]
  8. Coppock, A., Ekins, E., & Kirby, D. (2018). The long-lasting effects of newspaper op-eds on public opinion. Quarterly Journal of Political Science, 13 (1), 59-87.
    [Google Scholar]
  9. Dalton, R. J. (1987). Generational change in elite political beliefs: The growth of ideological polarization. Journal of Politics, 49 (4), 976-997.
    [Google Scholar]
  10. Doorn, M. van (2023). Waarom we beter denken dan we denken. Gorredijk: Noordhoek.
    [Google Scholar]
  11. Eck, C. W. van, Mulder, B. C., & Dewulf, A. (2020). Online climate change polarization: Interactional framing analysis of climate change blog comments. Science Communication, 42 (4), 454-480.
    [Google Scholar]
  12. Fiedler, K., & Unkelbach, C. (2014). Regressive judgment: Implications of a universal property of the empirical world. Current Directions in Psychological Science, 23 (5), 361-367.
    [Google Scholar]
  13. Hahn, U. (2020). Argument quality in real world argumentation. Trends in Cognitive Sciences, 24 (5), 363-374.
    [Google Scholar]
  14. Hahn, U., & Harris, A. J. L. (2014). What does it mean to be biased: rationality and motivated reasoning. In B.Ross (Ed.) The psychology of learning and motivation (pp. 41-102). London: Elsevier.
    [Google Scholar]
  15. Hoeken, H. (2023). Welke rol kan communicatie spelen bij het oplossen van grote maatschappelijke problemen?Tijdschrift voor Taalbeheersing, 45 (2/3), 217-243.
    [Google Scholar]
  16. Hoeken, H., & Vugt, M. van (2014). Het bevooroordeelde gebruik van argumentatiespecifieke criteria. Tijdschrift voor Taalbeheersing, 36 (1), 87-105.
    [Google Scholar]
  17. Hoeken, H., Hornikx, J., & Linders, Y. (2020). The importance and use of normative criteria to manipulate argument quality. Journal of Advertising, 49 (2), 195-201.
    [Google Scholar]
  18. Hoeken, H., Šorm, E., & Schellens, P. J. (2014). Arguing about the likelihood of consequences: Laypeople’s criteria to distinguish strong arguments from weak ones. Thinking and Reasoning, 20 (1), 77-98.
    [Google Scholar]
  19. Hornikx, J. (2014). Het effect van evidentiekwaliteit op de beoordeling van standpunten: de rol van toegevoegde tekst. Tijdschrift voor Taalbeheersing, 36 (1), 107-125.
    [Google Scholar]
  20. Hornikx, J. (2024). The impact of normative argument quality variations on claim acceptance: Empirical evidence from the US and the UK. Argumentation and Advocacy, 60 (1), 38-48.
    [Google Scholar]
  21. Iyengar, S., & Hahn, K. S. (2009). Red media, blue media: Evidence of ideological selectivity in media use. Journal of Communication, 59 (1), 19-39.
    [Google Scholar]
  22. Iyengar, S., Sood, G., Lelkes, Y. (2012). Affect, not ideology: A social identity perspective on polarization. Public Opinion Quarterly, 76 (3), 405-431.
    [Google Scholar]
  23. Kim, Y. (2019). How cross-cutting news exposure relates to candidate issue stance knowledge, political polarization, and participation: The moderating role of political sophistication. International Journal of Public Opinion Research, 31 (4), 626-648.
    [Google Scholar]
  24. Klaczynski, P., Gordon, D., & Fauth, J. (1997). Goal-oriented critical reasoning and individual differences in critical reasoning biases. Journal of Educational Psychology, 89 (3), 470-485.
    [Google Scholar]
  25. Kubin, E., & von Sikorski, C. (2021). The role of (social) media in political polarization: A systematic review. Annals of the International Communication Association, 45 (3), 188-206.
    [Google Scholar]
  26. Kuhn, D., & Lao, J. (1996). Effects of evidence on attitudes: Is polarization the norm?Psychological Science, 7 (2), 115-120.
    [Google Scholar]
  27. Kunda, Z. (1990). The case for motivated reasoning. Psychological Bulletin, 108 (3), 480-498.
    [Google Scholar]
  28. Levendusky, M. S. (2013). Why to partisan media polarize viewers? American Journal of Political Science, 57 (3), 611-623.
    [Google Scholar]
  29. Lorenz-Spreen, P., Oswald, L., Lewandowsky, S. & Hertwig, R. (2023). A systematic review of worldwide causal and correlational evidence on digital media and democracy. Nature Human Behavior, 7, 74-101.
    [Google Scholar]
  30. Mercier, H. (2020). Not born yesterday: The science of who we trust and what we believe. Princeton, NJ: Princeton University Press.
    [Google Scholar]
  31. Mercier, H., & Sperber, D. (2017). The enigma of reason. Cambridge, MA: Harvard University Press.
    [Google Scholar]
  32. Minson, J. A., & Chen, F. S. (2022). Receptiveness to opposing views: Conceptualization and integrative review. Personality and Social Psychology Review, 26 (2), 93-111.
    [Google Scholar]
  33. Minson, J. A., Chen, F. S., & Tinsley, C. H. (2020). Why won’t you listen to me? Measuring receptiveness to opposing views. Management Science, 66 (7), 3069-3094.
    [Google Scholar]
  34. Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2, 175-220.
    [Google Scholar]
  35. O’Keefe, D. J., & Hoeken, H. (2021). Message design choices don’t make much difference to persuasiveness and can’t be counted on – not even when moderating conditions are specified. Frontiers in Psychology, 12, 664160.
    [Google Scholar]
  36. Padgett, J., Dunaway, J. L., & Darr, J. P. (2019). As seen on TV? How gatekeeping makes the U.S. house seem more extreme. Journal of Communication, 69 (6), 696-719.
    [Google Scholar]
  37. Schmitt, J. B., Rieger, D., Rutkowski, O., & Ernst, J. (2018). Counter-messages as prevention or promotion of extremism?! The potential role of YouTube: Recommendation algorithms. Journal of Communication, 68 (4), 780-808.
    [Google Scholar]
  38. Webster, S. W., & Abramowitz, A. I. (2017). The ideological foundations of affective polarization in the U.S. electorate. American Politics Research, 45 (4), 621-647.
    [Google Scholar]
  39. Xu, M., & Petty, R. E. (2021). Two-sided messages promote openness for morally based attitudes. Personality and Social Psychology Bulletin, 48 (8), 1151-1166.
    [Google Scholar]
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