Zusammenfassung
So beschreibt Eli Pariser den Begriff der Filter Bubble (Filterblase), den er ein Jahr später mit seinem Buch Filter Bubble: Wie wir im Internet entmündigt werden geprägt hat. Es liegt ihm daran, auf mögliche Probleme hinzuweisen, die entstehen können, wenn über das Internet nur noch personalisierte Nachrichten zu finden sind. Richten sich Beiträge, die Nutzerinnen und Nutzer in sozialen Netzwerken sehen oder die sie über Suchmaschinen finden, nur noch nach deren Ansichten und Vorlieben, kann ein verzerrtes Bild der Wirklichkeit entstehen.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Literatur
Bakshy, E., Messing, S., & Adamic, L. A. (2015). Exposure to ideologically diverse news and opinion on Facebook. Science, 348, 1130–1132.
Barberá, P., Jost, J. T., Nagler, J., Tucker, J. A., & Bonneau, R. (2015). Tweeting from left to right: Is online political communication more than an echo chamber? Psychological Science, 26, 1531–1542.
Barnidge, M. (2017). Exposure to political disagreement in social media versus face-to-face and anonymous online settings. Political Communication, 34, 302–321.
Boutyline, A., & Willer, R. (2017). The social structure of political echo chambers: Variation in ideological homophily in inline networks. Political Psychology, 38, 551–569.
Boxell, L., Gentzkow, M., & Shapiro, J. (2017). Is the internet causing political polarization? Evidence from demographics (No. 23258).
Bozdag, E., Gao, Q., Houben, G. J., & Warnier, M. (2014). Does offline political segregation affect the filter bubble? An empirical analysis of information diversity for Dutch and Turkish Twitter users. Computers in Human Behavior, 41, 405–415.
Colleoni, E., Rozza, A., & Arvidsson, A. (2014). Echo chamber or public sphere? Predicting political orientation and measuring political homophily in Twitter using big data. Journal of Communication, 64, 317–332.
Flaxman, S., Goel, S., & Rao, J. M. (2016). Filter bubbles, echo chambers, and online news consumption. Public Opinion Quarterly, 80, 298–320.
Fletcher, R., & Nielsen, R. K. (2017). Are news audiences increasingly fragmented? A cross-national comparative analysis of cross-platform news audience fragmentation and duplication. Journal of Communication, 67, 476–498.
Garrett, R. K. (2009). Echo chambers online?: Politically motivated selective exposure among Internet news users. Journal of Computer-Mediated Communication, 14, 265–285.
Hart, W., Albarracín, D., Eagly, A. H., Brechan, I., Lindberg, M. J., & Merrill, L. (2009). Feeling validated versus being correct: A meta-analysis of selective exposure to information. Psychological Bulletin, 135, 555–588.
Helberger, N., Karppinen, K., & D’Acunto, L. (2018). Exposure diversity as a design principle for recommender systems. Information Communication and Society, 21, 191–207.
Jacobson, S., Myung, E., & Johnson, S. L. (2016). Open media or echo chamber: The use of links in audience discussions on the Facebook pages of partisan news organizations. Information Communication and Society, 19, 875–891.
Lazer, D. (2015). The rise of the social algorithm. Science, 348, 1090–1091.
Nagulendra, S., & Vassileva, J. (2016). Providing awareness, explanation and control of personalized filtering in a social networking site. Information Systems Frontiers, 18, 145–158.
Nikolov, D., Oliveira, D. F. M., Flammini, A., & Menczer, F. (2015). Measuring online social bubbles. PeerJ Computer Science, 1.
Pariser, E. (2011). Eli Pariser: Beware online “Filter Bubbles.” https://www.ted.com/talks/eli_pariser_beware_online_filter_bubbles?language=en.
Pariser, E. (2012). Filter Bubble: Wie wir im Internet entmündigt werden. München: Hanser.
Tucker, J. A., Guess, A., Barbera, P., Vaccari, C., Siegel, A., Sanovich, S., et al. (2018). Social media, political polarization, and political disinformation: A review of the scientific literature. SSRN Electronic Journal, 1–95.
Webster, J. G., & Ksiazek, T. B. (2012). The dynamics of audience fragmentation: Public attention in an age of digital media. Journal of Communication, 62, 39–56.
Yom-Tov, E., Dumais, S., & Guo, Q. (2014). Promoting civil discourse through search engine diversity. Social Science Computer Review, 32, 145–154.
Zillmann, D. (2000). Mood management in the context of selective exposure theory. Annals of the International Communication Association, 23, 103–123.
Zuiderveen Borgesius, F. J., Trilling, D., Möller, J., Bodó, B., de Vreese, C. H., & Helberger, N. (2016). Should we worry about filter bubbles? Internet Policy Review, 5, 1–16.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature
About this chapter
Cite this chapter
Messingschlager, T., Holtz, P. (2020). Filter Bubbles und Echo Chambers. In: Appel, M. (eds) Die Psychologie des Postfaktischen: Über Fake News, „Lügenpresse“, Clickbait & Co.. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-58695-2_9
Download citation
DOI: https://doi.org/10.1007/978-3-662-58695-2_9
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-58694-5
Online ISBN: 978-3-662-58695-2
eBook Packages: Psychology (German Language)