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Digital Bubbles: Living in Accordance with Personalized Seclusions and Their Effect on Critical Thinking

  • Beatriz Ribeiro
  • Cristiana Gonçalves
  • Francisco Pereira
  • Gonçalo Pereira
  • Joana Santos
  • Ramiro Gonçalves
  • Manuel Au-Yong-OliveiraEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 932)

Abstract

Since the emergence of the Global Village, the information flow changed drastically. Digital Technologies changed how people communicate, how they access information and how they share it. It gave people an unlimited exposure to information and knowledge. However, it also seemed to limit it. Recommendation algorithms are used in order to provide a customized experience that captivates users. Although they play an important role in selecting information that is considered relevant to the user, significant information/content may be omitted. Consequently, users end up closed in a bubble of limited information, which affects critical thinking skills and appears to influence and guide personal opinions. Little attention has been given to the negative effects of information bias on people’s critical thinking. Thus, it is hoped that this study will at the same time educate and bring awareness to this issue. In a survey we performed (with 117 answers) the majority of the survey sample (approximately 54,7%) revealed discomfort regarding the storage and filtering of data. Interestingly, 29,9% of the participants were found to be indifferent regarding this issue. From these results, the authors can conclude that, although most of the participants feel uncomfortable, they prefer to be passive about this, which reinforces the idea of conformity and the false sense of organization mentioned herein. An interview with an expert in the area drew attention to the fact that social pressure most often leads users to comply and rely on the group’s beliefs and attitudes, which facilitates social relationships and avoids confrontation.

Keywords

Technology Filter bubble Critical thinking Social media Algorithms Rational behaviour News feed Information Online Customization 

Notes

Acknowledgements

The authors would like to thank everyone who took their time to respond to the survey questionnaire. We would also like to gratefully acknowledge the help provided by Dr Amanda Franco, at CIDTFF (Department of Education and Psychology of the University of Aveiro, Portugal). Her sharing of knowledge regarding critical thinking has proven to be fundamental to the authors’ approach to the subject.

References

  1. 1.
    Gonçalves, R., Martins, J., Pereira, J., Cota, M., Branco, F.: Promoting e-commerce software platforms adoption as a means to overcome domestic crises: the cases of Portugal and Spain approached from a focus-group perspective. In: Trends and Applications in Software Engineering, pp. 259–269. Springer, Cham (2016)Google Scholar
  2. 2.
    Martins, J., Gonçalves, R., Pereira, J., Cota, M.: Iberia 2.0: a way to leverage Web 2.0 in organizations. In: 2012 7th Iberian Conference on Information Systems and Technologies (CISTI), pp. 1–7. IEEE (2012)Google Scholar
  3. 3.
    Gonçalves, R., Martins, J., Branco, F., Perez-Cota, M., Au-Yong-Oliveira, M.: Increasing the reach of enterprises through electronic commerce: a focus group study aimed at the cases of Portugal and Spain. Comput. Sci. Inf. Syst. 13, 927–955 (2016)CrossRefGoogle Scholar
  4. 4.
    Bozdag, E.: Bias in algorithmic filtering and personalization. Ethics Inf. Technol. 15(3), 209–227 (2011)CrossRefGoogle Scholar
  5. 5.
    Pariser, E.: The Filter Bubble - What is the Internet Hiding from You. Viking, Penguin Books, London (2011)Google Scholar
  6. 6.
    Moeller, J., Helberger, N.: Beyond the filter bubble: concepts, myths, evidence and issues for future debates (2018). https://www.ivir.nl/publicaties/download/Beyond_the_filter_bubble__concepts_myths_evidence_and_issues_for_future_debates.pdf
  7. 7.
    Courtois, C., Slechten, L., Coenen, L.: Challenging Google Search filter bubbles in social and political information: disconforming evidence from a digital methods case study. Telematics Inform. 35(7), 2006–2015 (2018).  https://doi.org/10.1016/j.tele.2018.07.004CrossRefGoogle Scholar
  8. 8.
    Bozdag, E., van den Hoven, J.: Breaking the filter bubble: democracy and design. Ethics Inf. Technol. 17(4), 249–265 (2015).  https://doi.org/10.1007/s10676-015-9380-yCrossRefGoogle Scholar
  9. 9.
    Garrett, R.K.: The “Echo Chamber” distraction: disinformation campaigns are the problem, not audience fragmentation. J. Appl. Res. Mem. Cogn. 6(4), 370–376 (2017).  https://doi.org/10.1016/j.jarmac.2017.09.011CrossRefGoogle Scholar
  10. 10.
    Nechushtai, E., Lewis, S.C.: 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 (2019).  https://doi.org/10.1016/j.chb.2018.07.043CrossRefGoogle Scholar
  11. 11.
    Kiszl, P., Fodor, J.: The “Collage Effect” – against filter bubbles: interdisciplinary approaches to combating the pitfalls of information technology. J. Acad. Librarianship (2018).  https://doi.org/10.1016/j.acalib.2018.09.020
  12. 12.
    Lazer, D.M.J., Baum, M.A., Benkler, Y., Berinsky, A.J., Greenhill, K.M., Menczer, F., Metzger, M.J., Nyhan, B., Pennycook, G., Rothschild, D., Schudson, M., Sloman, S.A., Sunstein, C.R., Thorson, E.A., Watts, D.J., Zittrain, J.L.: The science of fake news: addressing fake news requires a multidisciplinary effort. Science 359(6380), 1094–1096 (2018).  https://doi.org/10.1126/science.aao2998CrossRefGoogle Scholar
  13. 13.
    Geschke, D., Lorenz, J., Holtz, P.: The triple-filter bubble: using agent-based modelling to test a meta-theoretical framework for the emergence of filter bubbles and echo chambers. Br. J. Soc. Psychol., 1–21 (2018).  https://doi.org/10.1111/bjso.12286
  14. 14.
    Miller, M.K., Clark, J.D., Jehle, A.: Cognitive Dissonance Theory (Festinger) (2015)Google Scholar
  15. 15.
    McMurray, A.: Research: A Common-Sense Approach. Cengage Learning Australia, Cengage (2004)Google Scholar
  16. 16.
    Loudon, D.L., Della Britta, A.J.: Consumer Behaviour: Concepts and Applications. McGraw Hill, New York (1979)Google Scholar
  17. 17.
    Shuford, E., Kavanaugh T., Ralph, B., Ceesay, E., Watters, P.: Measuring personal privacy breaches using third-party trackers (2018). https://www.researchgate.net/publication/303488658

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Beatriz Ribeiro
    • 1
  • Cristiana Gonçalves
    • 1
  • Francisco Pereira
    • 1
  • Gonçalo Pereira
    • 1
  • Joana Santos
    • 1
  • Ramiro Gonçalves
    • 2
  • Manuel Au-Yong-Oliveira
    • 3
    Email author
  1. 1.Department of Languages and CulturesUniversity of AveiroAveiroPortugal
  2. 2.INESC TEC and University of Trás-os-Montes e Alto DouroVila RealPortugal
  3. 3.GOVCOPP, Department of Economics, Management, Industrial Engineering and TourismUniversity of AveiroAveiroPortugal

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