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People see what they want to see: an EEG study

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Abstract

This study explored selective exposure and confirmation bias in the choices participants made about which political videos to watch, and whether their political positions changed after they watched videos that either agreed with or opposed their positions on two controversial issues in South Korea: North Korea policy and social welfare policy. The participants completed questionnaires before and after they watched the videos, were asked to select thumbnails of videos before they watched any, and had their brain wave activity measured through electroencephalogram (EEG) as they watched both types of videos. The participants demonstrated selective exposure as they primarily selected video thumbnails with content that matched their political orientations, and they demonstrated confirmation bias as their questionnaire responses after they watched the videos indicated that their positions had hardened. There were also statistically significant differences in alpha, beta, sensory motor rhythm, low beta, mid beta, and fast alpha activity depending on the political orientation consistency between the participants and the videos. Future studies could expand this line of research beyond college students and beyond Asia, and longitudinal work could also be conducted to determine if the obtained patterns remain constant over time.

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Data Availability

Raw Data were generated at Sungkyunkwan University. Derived data supporting the findings of this study are available from the corresponding author on request.

References

  • Bartikowski B, Walsh G (2011) Investigating mediators between corporate reputation and customer citizenship behaviors. J Bus Res 64(1):39–44

  • Baumgartner JC, Morris JS (2010) MyFaceTube politics: social networking web sites and political engagement of young adults. Soc Sci Comput Rev 28(1):24–44

    Article  Google Scholar 

  • Beam MA (2014) Automating the news: How personalized news recommender system design choices impact news reception. Commun Res 41(8):1019–1041

    Article  Google Scholar 

  • Bessi A, Coletto M, Davidescu GA, Scala A, Caldarelli G, Quattrociocchi W (2015) Science vs conspiracy: collective narratives in the age of misinformation. PLoS ONE 10(2):e0118093

    Article  PubMed  PubMed Central  Google Scholar 

  • Bolse T, Druckman JN, Cook FL (2014) The influence of partisan motivated reasoning on public opinion. Polit Behav 36:235–262

  • Bozdag E, Gao Q, Houben GJ, Warnier M (2014) Does offline political segregation affect the filter bubble? An empirical analysis of information diversity for Dutch and Turkish Twitter users. Comput Hum Behav 41:405–415

    Article  Google Scholar 

  • Brugnoli E, Cinelli M, Quattrociocchi W, Scala A (2019) Recursive patterns in online echo chambers. Sci Rep 9(1):1–18

    Article  Google Scholar 

  • Butler S (1988) Alpha asymmetry, hemispheric specialization and the problem of cognitive dynamics. In: The EEG of mental activities Karger Publishers, pp 75–93

  • Chariter D, Chariter L (2003) QEEG assessment of traumatic brain injury and stroke patients. J Neurother 7(1):113–134

    Google Scholar 

  • Ching TH, Tang CS (2016) Cognitive dissonance about thought-action fusion beliefs improves and maintains the effects of thought-action fusion-specific psychoeducation. J Cogn Psychother 30(4):235–252

    Article  PubMed  Google Scholar 

  • Cho J, Ahmed S, Hilbert M, Liu B, Luu J (2020) Do search algorithms endanger democracy? An experimental investigation of algorithm effects on political polarization. J Broadcast Electron Media 64(2):150–172

    Article  Google Scholar 

  • Choi JS (2020) Re-examining ‘the Phenomenon of 20s Male’: focused on the ideological orientation and gender consciousness of people in their 20s, 30s, 40s. Econ Soc 125:189–224

    Google Scholar 

  • Colosio M, Shestakova A, Nikulin V, Shpektor A, Klucharev V (2015) Neural mechanisms of the postdecisional spreading-of-alternatives effect: EEG study. Higher School of Economics Research Paper No, WP BRP, p 50

    Google Scholar 

  • Colosio M, Shestakova A, Nikulin VV, Blagovechtchenski E, Klucharev V (2017) Neural mechanisms of cognitive dissonance (revised): an EEG study. J Neurosci 37(20):5074–5083

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Covington P, Adams J, Sargin E (2016) Deep neural networks for youtube recommendations. In: Proceedings of the 10th ACM conference on recommender systems, pp 191–198

  • Cowan J, Allen T (2000) Using brainwave biofeedback to train the sequence of concentration and relaxation in athletic activities. In: Proceedings of 15th Association for the advancement of applied sport psychology, p 95

  • Della Rocchetta AI, Milner B (1993) Strategic search and retrieval inhibition: The role of the frontal lobes. Neuropsychologia 31(6):503–524

  • Fuster JM (1980) The prefrontal cortex: anatomy. Physiology and Neuropsychology of the Frontal Lobe.

  • De Houwer J, Gawronski B, Barnes-Holmes D (2013) A functional-cognitive framework for attitude research. Eur Rev Soc Psychol 24(1):252–287

    Article  Google Scholar 

  • Djerf-Pierre M, Lindgren M, Budinski MA (2019) The role of journalism on YouTube: audience engagement with" Superbug" reporting. Media Commun 7(1):235–247

    Article  Google Scholar 

  • Druckman JN, McGrath MC (2019) The evidence for motivated reasoning in climate change preference formation. Nat Clim Chang 9(2):111–119

  • Eagly AH, Chaiken S (2005) Attitude research in the 21st century: the current state of knowledge

  • Egner T, Gruzelier JH (2004) EEG biofeedback of low beta band components: frequency-specific effects on variables of attention and event-related brain potentials. Clin Neurophysiol 115(1):131–139

    Article  CAS  PubMed  Google Scholar 

  • Fairclough SH, Venables L, Tattersall A (2005) The influence of task demand and learning on the psychophysiological response. Int J Psychophysiol 56(2):171–184

    Article  PubMed  Google Scholar 

  • Festinger L (1957) A theory of cognitive dissonance, vol 2. Stanford University Press, Redwood City

    Book  Google Scholar 

  • Festinger L (1962) Cognitive dissonance. Sci Am 207(4):93–106

    Article  CAS  PubMed  Google Scholar 

  • Fischer P, Reinweber M, Vogrincic C, Schäfer A, Schienle A, Volberg G (2013) Neural mechanisms of selective exposure: an EEG study on the processing of decision-consistent and inconsistent information. Int J Psychophysiol 87(1):13–18

    Article  PubMed  Google Scholar 

  • Garimella K, De Francisci Morales G, Gionis A, Mathioudakis M (2018) Political discourse on social media: Echo chambers, gatekeepers, and the price of bipartisanship. In: Proceedings of the 2018 World Wide Web Conference, pp 913–922

  • Gaskell GD, Wright DB, O’Muircheartaigh C (1995) Context effects in the measurement of attitudes: a comparison of the consistency and framing explanations. Br J Soc Psychol 34(4):383–393

    Article  CAS  Google Scholar 

  • Goldman-Rakic PS (1994) Specification of higher cortical functions. In: Atypical cognitive deficits in developmental disorders: Implications for brain function, p 3–17

  • Haim M, Graefe A, Brosius HB (2018) Burst of the filter bubble? Effects of personalization on the diversity of Google News. Digit J 6(3):330–343

    Google Scholar 

  • Harmon-Jones E, Clarke D, Paul K, Harmon-Jones C (2020) The effect of perceived effort on reward valuation: Taking the reward Positivity (RewP) to dissonance theory. Front Hum Neurosci 14:157

    Article  PubMed  PubMed Central  Google Scholar 

  • Harmon-Jones EE, Mills JE (1999) Cognitive dissonance: progress on a pivotal theory in social psychology. In: scientific conferences program, 1997, U Texas, Arlington, TX, US; This volume is based on papers presented at a 2-day conference at the University of Texas at Arlington, winter 1997. American Psychological Association

  • Hart W, Albarracín D, Eagly AH, Brechan I, Lindberg MJ, Merrill L (2009) Feeling validated versus being correct: a meta-analysis of selective exposure to information. Psychol Bull 135(4):555

    Article  PubMed  PubMed Central  Google Scholar 

  • Herek GM, Capitanio JP (1999) AIDS stigma and sexual prejudice. Am Behav Sci 42(7):1130–1147

    Article  Google Scholar 

  • Hippler HJ, Schwarz N, Sudman S (eds) (2012) Social information processing and survey methodology. Springer, Berlin

    Google Scholar 

  • Hutchison M (1986) Megabrain: New tools and techniques for brain growth and mind expansion. William Morrow & Company

  • Iyengar S, McGrady J (2007) Media politics: A citizen’s guide. WW Norton, New York

    Google Scholar 

  • Kappes A, Harvey AH, Lohrenz T, Montague PR, Sharot T (2020) Confirmation bias in the utilization of others’ opinion strength. Nat Neurosci 23(1):130–137

    Article  CAS  PubMed  Google Scholar 

  • Kim OS, Lee SW (2015) A Movie Recommendation Method based on Emotion Ontology. J Korea Multimed Soc 18(9):1068–1082

  • Kim SH (2021) Developing a VR-EEG-based Model for Optimizing Visual Perceptual Components of Healing Space. Dissertaion, Kyungpook national university

  • Klimesch W, Sauseng P, Hanslmayr S (2007) EEG alpha oscillations: the inhibition–timing hypothesis. Brain Res Rev 53(1):63–88

    Article  PubMed  Google Scholar 

  • Lee S, Ahn J, Jeong I, Kim K (2014) Vitalization of EEG according fear, humor, sex appeal in advertising and the relation to EEG with recall about advertising. Advert Res 101:62–94

    Google Scholar 

  • Lee SE (2011) Effect of Volatile Fragrance Components of Citrus aurantiifolia and Eugenia caryophylla on Electroencephalogram. Dissertaion, Kangwon national university

  • Lundgren SR, Prislin R (1998) Motivated cognitive processing and attitude change. Pers Soc Psychol Bull, 24(7):715–726

  • MacKenzie SB, Lutz RJ (1989) An empirical examination of the structural antecedents of attitude toward the ad in an advertising pretesting context. J Mark 53(2):48–65

    Article  Google Scholar 

  • Moravec P, Minas R, Dennis AR (2018) Fake news on social media: People believe what they want to believe when it makes no sense at all. Kelley School of Business Research Paper, (18–87)

  • Nechushtai E, Lewis SC (2019) What kind of news gatekeepers do we want machines to be? Filter bubbles, fragmentation, and the normative dimensions of algorithmic recommendations. Comput Hum Behav 90:298–307

    Article  Google Scholar 

  • NetMarketShare (2021) Market share statistics for internet technologies. Retrieved from https://netmarketshare.com/. Accessed 12 Sept 2021

  • Newman N, Fletcher R, Schulz A, Andi S, Robertson CT, Nielsen RK (2021) Reuters institute digital news report 2021. Reuters Institute for the Study of Journalism

  • Nickerson RS (1998) Confirmation bias: a ubiquitous phenomenon in many guises. Rev Gen Psychol 2(2):175–220

    Article  Google Scholar 

  • Pariser E (2011) The filter bubble: What the Internet is hiding from you. Penguin UK, London

    Google Scholar 

  • Pew Research Center (2020) Americans who mainly get their news on social media are less engaged, less knowledgeable. Retrieved from https://www.pewresearch.org/journalism/2020/07/30/americans-who-mainly-get-their-news-on-social-media-are-less-engaged-less-knowledgeable/. Accessed 30 July 2020

  • Quattrociocchi W, Scala A, Sunstein CR (2016) Echo chambers on Facebook. SSRN Electron J. https://doi.org/10.2139/ssrn.2795110

    Article  Google Scholar 

  • Ray WJ (1990) The electrocortical system. Principles of psychophysiology.

  • Ricci F, Rokach L, Shapira B (2011) Introduction to recommender systems handbook. recommender systems handbook. Springer, Boston, MA, pp 1–35

    Chapter  Google Scholar 

  • Sanei S, Chambers JA (2013) EEG signal processing. John Wiley & Sons

  • Sayorwan W, Siripornpanich V, Piriyapunyaporn T, Hongratanaworakit T, Kotchabhakdi N, Ruangrungsi N (2012) The effects of lavender oil inhalation on emotional states, autonomic nervous system, and brain electrical activity

  • Severin WJ, Tankard JW (2004) Communication methods and uses in mass media

  • Shin YJ, Lee SW (2021) An analysis of filter bubble phenomenon on YouTube recommendation algorithm using text mining. J Korea Contents Assoc 21(5):1–10

    Google Scholar 

  • Stanovich KE, West RF (2007) Natural myside bias is independent of cognitive ability. Think Reason 13(3):225–247

    Article  Google Scholar 

  • Subha DP, Joseph PK, Acharya UR, Lim CM (2010) EEG signal analysis: a survey. J Med Syst 34:195–212

  • Sumiala JM, Tikka M (2013) Broadcast yourself—global news! a netnography of the “flotilla” news on YouTube. Commun Cult Crit 6(2):318–335

    Article  Google Scholar 

  • Sunstein CR (2007) Republic.com 2.0. Princeton University Press Pub, Princeton

    Google Scholar 

  • Sutton SK, Davidson RJ (1997) Prefrontal brain asymmetry: A biological substrate of the behavioral approach and inhibition systems. Psychol Sci 8(3):204–210

  • Tubefilter (2019). https://www.tubefilter.com/2018/01/11/youtube-most-watch-time-driven-by-recommendations/

  • Wheeler RE, Davidson RJ, Tomarken AJ (1993) Frontal brain asymmetry and emotional reactivity: A biological substrate of affective style. Psychophysiol 30(1):82–89

  • Wildes TS, Avidan MS (2019) Critical appraisal of ENGAGES: cognitive dissonance and anesthesia research. Ann Trans Med 7(20):599–599. https://doi.org/10.21037/atm.2019.09.48

    Article  Google Scholar 

  • WISEAPP (2021) The generation who uses YouTube the most on their smartphones is in their 50s and older. https://www.wiseapp.co.kr/insight/detail/36. Accessed 11 Jun 2023

  • Yu H, Ryoo Y, Han E (2023) Mind over matter: how biased perceptions of political knowledge influence selection and evaluation of political YouTube channels. Internet Res. https://doi.org/10.1108/INTR-09-2021-0677

    Article  Google Scholar 

  • Yun S, Rhee M (2014) Ideological conflict in young and older generations: differences in ideology determinants and ideology representation. 21st Centry Polit Sci Rev 24(3):271–292

    Article  Google Scholar 

  • ZERO LIMIT WEB (2021) Part 1: organic vs PPC in 2021: the CTR results. Retrieved from https://www.zerolimitweb.com/organic-vs-ppc-2021-ctr-results-best-practices/. Accessed 7 Feb 2021

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Yu, H., Han, E. People see what they want to see: an EEG study. Cogn Neurodyn (2023). https://doi.org/10.1007/s11571-023-09982-8

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