Araştırma Makalesi
BibTex RIS Kaynak Göster

THE CRITICISM OF PERSONALIZED ONLINE NEWS FEED: ECHO CHAMBER EFFECT, FILTER BUBBLE AND CYBERBALCANIZATION

Yıl 2018, Cilt: 11 Sayı: 2, 232 - 251, 11.07.2018
https://doi.org/10.18094/josc.340471

Öz











The aim of this research is to explain the
concept and types of personalized online news, as well as providing a holistic
view by presenting different views on this distinctive feature of the new media
with literature review. In this context, the study firstly focuses on the basic
working logic of algorithms that primarily provide personalized news content. Subsequently,
the assumptions of critical works on the automatic creation of personal news feeds
are discussed in the context of echo chamber effect, filter bubble, and
cyberbalkanization concepts.
Finally, the
comparison of different approaches in the literature is provided by presenting
the results of empirical studies in which the criticisms are found to be
overhyped.
The study also
describes the technological tools which are developed to solve the problems
that may be caused by the personalized news. At the end of the research, it was
emphasized that journalistic ethics should be improved to include transparency
of technological processes of news personalization as well as media ownership
and news content.
Media literacy courses
have also been proposed to cover these topics.

Kaynakça

  • Adar E, Gearig C, Balasubramanian A ve Hullman J (2017) PersaLog: Personalization of News Article Content, CHI 2017, May 6–11, Denver, CO, USA, 3188-3200.
  • Anand B N (2017) The U.S. Media’s Problems Are Much Bigger than Fake News and Filter Bubbles, Harvard Business Review, 2-10. Baron D P (1994) Electoral Competition with Informed and Uninformed Voters, American Political Science Review, 88: 33–47.
  • Beam M A (2014) Automating the News: How Personalized News Recommender System Design Choices Impact News Reception, Communication Research, Vol. 41(8), 1019–1041.
  • Beam M A ve Kosicki G M (2014) Personalized News Portals: Filtering Systems and Increased News Exposure, Journalism & Mass Communication Quarterly, Vol. 91(1), 59–77.
  • Binark M (2017) Algoritmaların Yarattığı Yankı Odaları ve Siyasal Katılım Olanağı veya Olanaksızlığı, Varlık Dergisi, Sayı 1317, Haziran 2017, 19-23.
  • Bozdag E, Gao Q, Houben, G, Warnier M (2014) Computers in Human Behavior 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.
  • Chen C, Meng X, Xu Z, ve Lukasiewicz T (2017). Location-Aware Personalized News Recommendation With Deep Semantic Analysis, IEEE, 2169-3536.
  • 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, s. 317–332.
  • Constine J (2016) How Facebook News Feed Works, https://techcrunch.com/2016/09/06/ultimate-guide-to-the-news-feed/ erişim tarihi: 06.06.2017
  • Dutton W, Reisdorf W C, Dubois E, Blak, G (2017) Search and Politics: The Uses and Impacts of Search in Britain, France, Germany, Italy, Poland, Spain, and the United States, Quello Center Working Paper, No. 5-1-17.
  • Dutton, W (2017) Fake news, echo chambers and filter bubbles: Underresearched and overhyped, The Conversation, 05.05.2017, http://theconversation.com/fake-news-echo-chambers-and-filter-bubbles-underresearched-and-overhyped-76688 , erişim tarihi: 11.06.2017
  • Festinger L (1957) A Theory of Cognitive Dissonance. Evanston, IL: Row, Peterson.
  • Flaxman S, Goel S ve Rao J M (2016) Filter Bubbles, Echo Chambers, and Online News Consumption, Public Opinion Quarterly, Vol. 80, Special Issue, 298–320.
  • Gearig C, Adar E, Hullman J (2015) Designing for Personalized Article Content, Computation + Journalism (C+J), 1-5.
  • Goel S, Hofman J M ve Sirer M I (2012) Who Does What on the Web: A Large-Scale Study of Browsing Behavior, Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media, 1–8.
  • Gunter B (2003) News and the Net, Lawrence Erlbaum Associates, Inc. Publishers, USA.
  • Hess A (2017) How to Escape Your Political Bubble for a Clearer View, https://www.nytimes.com/2017/03/03/arts/the-battle-over-your-political-bubble.html?_r=0, erişim tarihi: 06.06.2017
  • Hindman M (2012). Personalization and the Future of News, EUI Working Paper RSCAS 2012/56, 1-14.
  • Iyengar S ve Hahn K S (2009) Red media, blue media: Evidence of ideological selectivity in media use, Journal of Communication, 59, 19-39.
  • Jones D A (2002). The Polarization Effect of New Media Message, International Journal of Public Opinion Research, 14, 158–174.
  • Lassen D D (2005) The Effect of Information on Voter Turnout: Evidence from a Natural Experiment, American Journal of Political Science, 49: 103–18.
  • Moeller J, Trilling D, Helberger N, Irion K ve De Vreese C. (2016) Shrinking core? Exploring the differential agenda setting power of traditional and personalized news media, info, Vol. 18, Issue: 6, 26-41.
  • Mostafa J (2002) Information Customization. Intelligent Systems, IEEE, 17(6), 8–11.
  • Negroponte N (1995) Being Digital, Knopf Doubleday Publishing Group, New York
  • Obendorf H, Harald W, Eelco H ve Matthias M (2007) Web Page Revisitation Revisited: Implications of a Long-Term Click-Stream Study of Browser Usage, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 597–606.
  • Pariser E (2011) The Filter Bubble: What the Internet is Hiding From You. New York, Penguin.
  • Pons A (2013) Beyond deliberation and cyber-balkanization, Master Thesis, Erasmus University Rotterdam
  • Putnam R D (2000). Bowling alone: The collapse and revival of American community, New York, Simon & Schuster
  • Rainie L (2009) The new news audience, http://www.pewinternet.org/2009/11/13/the-new-news-audience/, erişim tarihi: 22.06.2017
  • Rimer B K ve Kreuter M W (2006) Advancing tailored health communication: A persuasion and message effects perspective, Journal of Communication, 56, 184-201.
  • Roberto A J, Krieger J L ve Beam M A (2009) Enhancing web-based prevention messages for Hispanics using targeting and tailoring, Journal of Health Communication, 14, 525-540.
  • Suhay E.,  Blackwell A,  Roche C, Bruggeman L (2015) Forging Bonds and Burning Bridges: Polarization and Incivility in Blog Discussions About Occupy Wall Street, American Politics Research, Vol. 43(4), 643–679.
  • Sundar S S ve Marathe S S (2010) Personalization versus Customization: The Importance of Agency, Privacy, and Power Usage, Human Communication Research, 36, 298–322.
  • Sunstein C (2001) Republic.com 2.0. Princeton, NJ: Princeton University Press.
  • Sunstein C (2004) Democracy and Filtering, December 2014, Vol. 47, No.12, 57-59.
  • Sunstein C (2009) Republic.com 2.0. Princeton, NJ: Princeton University Press.
  • VanAlstyne M ve Brynjolffson E (2005) Global village or cyber-balkans? Modeling and measuring the integration of electronic communities, Management Science, 51, 851–868.
  • Van Cuilenburg J ve McQuail D (2003) Media policy paradigm shifts: Towards a new communications policy paradigm, European Journal of Communication, 18, 181–207.
  • Van Dijk J (2016) Ağ Toplumu, Özlem Sakin (çev), Kafka, İstanbul.
  • Vesanen J (2007) What is personalization? A conceptual framework. European Journal of Marketing, 41, 409-418.
  • Vydiswaran V G V ve Chandrasekar R (2010) Improving the Online News Experience, HCIR’10, August 22, New Brunswick, NJ, USA, 1-4.
  • Wind J ve Rangaswamy A (2001) Customerization: The Next Revolution in Mass Customization, Journal of Interactive Marketing, 15, 13-32.
  • Zheng L, Li L, Hong W, Li T (2013) PENETRATE: Personalized news recommendation using ensemble hierarchical clustering, Expert Systems with Applications 40, 2127–2136.

Kişiselleştirilmiş Çevrimiçi Haber Akışının Yankı Odası Etkisi, Filtre Balonu ve Siberbalkanizasyon Kavramları Çerçevesinde İncelenmesi

Yıl 2018, Cilt: 11 Sayı: 2, 232 - 251, 11.07.2018
https://doi.org/10.18094/josc.340471

Öz











Bu araştırmanın amacı hem kişiselleştirmiş çevrimiçi haber
kavramını ve türlerini açıklamak hem de yeni medyanın ayırt edici bu özelliğine
yönelik farklı görüşleri literatür taraması ile serimleyerek bütüncül bir bakış
açısı sağlamaktır. Bu kapsamda, çalışmada öncelikle kişiselleştirilmiş haber
içerikleri sunan algoritmaların temel çalışma mantığı üzerinde durulmuştur.
Ardından kişisel haber akışlarının otomatik oluşturulmasına yönelik eleştirel
çalışmaların varsayımları yankı odası etkisi, filtre balonu ve
siberbalkanizasyon kavramları bağlamında tartışılmıştır. Son olarak, bu araştırmalardaki
eleştirileri iddialı bulan deneysel çalışmaların sonuçları sunularak; literatürdeki
farklı yaklaşımların karşılaştırılması sağlanmıştır. Çalışmada ayrıca kişiselleştirilmiş
haberlerin neden olabileceği sorunlardan korunmak için geliştirilen teknolojik araçlar
da açıklanmıştır. Araştırmanın sonunda, gazetecilik etiğinin medya sahiplik
yapısı ve içeriğe yönelik kodların yanı sıra kişiselleştirilmiş haber akışı
gibi teknolojik süreçlerin şeffaflığını da içerecek şekilde geliştirilmesi
gerektiği vurgulanarak; dijital medya okuryazarlığı derslerinin bu konuları da kapsaması
önerilmiştir.  

Kaynakça

  • Adar E, Gearig C, Balasubramanian A ve Hullman J (2017) PersaLog: Personalization of News Article Content, CHI 2017, May 6–11, Denver, CO, USA, 3188-3200.
  • Anand B N (2017) The U.S. Media’s Problems Are Much Bigger than Fake News and Filter Bubbles, Harvard Business Review, 2-10. Baron D P (1994) Electoral Competition with Informed and Uninformed Voters, American Political Science Review, 88: 33–47.
  • Beam M A (2014) Automating the News: How Personalized News Recommender System Design Choices Impact News Reception, Communication Research, Vol. 41(8), 1019–1041.
  • Beam M A ve Kosicki G M (2014) Personalized News Portals: Filtering Systems and Increased News Exposure, Journalism & Mass Communication Quarterly, Vol. 91(1), 59–77.
  • Binark M (2017) Algoritmaların Yarattığı Yankı Odaları ve Siyasal Katılım Olanağı veya Olanaksızlığı, Varlık Dergisi, Sayı 1317, Haziran 2017, 19-23.
  • Bozdag E, Gao Q, Houben, G, Warnier M (2014) Computers in Human Behavior 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.
  • Chen C, Meng X, Xu Z, ve Lukasiewicz T (2017). Location-Aware Personalized News Recommendation With Deep Semantic Analysis, IEEE, 2169-3536.
  • 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, s. 317–332.
  • Constine J (2016) How Facebook News Feed Works, https://techcrunch.com/2016/09/06/ultimate-guide-to-the-news-feed/ erişim tarihi: 06.06.2017
  • Dutton W, Reisdorf W C, Dubois E, Blak, G (2017) Search and Politics: The Uses and Impacts of Search in Britain, France, Germany, Italy, Poland, Spain, and the United States, Quello Center Working Paper, No. 5-1-17.
  • Dutton, W (2017) Fake news, echo chambers and filter bubbles: Underresearched and overhyped, The Conversation, 05.05.2017, http://theconversation.com/fake-news-echo-chambers-and-filter-bubbles-underresearched-and-overhyped-76688 , erişim tarihi: 11.06.2017
  • Festinger L (1957) A Theory of Cognitive Dissonance. Evanston, IL: Row, Peterson.
  • Flaxman S, Goel S ve Rao J M (2016) Filter Bubbles, Echo Chambers, and Online News Consumption, Public Opinion Quarterly, Vol. 80, Special Issue, 298–320.
  • Gearig C, Adar E, Hullman J (2015) Designing for Personalized Article Content, Computation + Journalism (C+J), 1-5.
  • Goel S, Hofman J M ve Sirer M I (2012) Who Does What on the Web: A Large-Scale Study of Browsing Behavior, Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media, 1–8.
  • Gunter B (2003) News and the Net, Lawrence Erlbaum Associates, Inc. Publishers, USA.
  • Hess A (2017) How to Escape Your Political Bubble for a Clearer View, https://www.nytimes.com/2017/03/03/arts/the-battle-over-your-political-bubble.html?_r=0, erişim tarihi: 06.06.2017
  • Hindman M (2012). Personalization and the Future of News, EUI Working Paper RSCAS 2012/56, 1-14.
  • Iyengar S ve Hahn K S (2009) Red media, blue media: Evidence of ideological selectivity in media use, Journal of Communication, 59, 19-39.
  • Jones D A (2002). The Polarization Effect of New Media Message, International Journal of Public Opinion Research, 14, 158–174.
  • Lassen D D (2005) The Effect of Information on Voter Turnout: Evidence from a Natural Experiment, American Journal of Political Science, 49: 103–18.
  • Moeller J, Trilling D, Helberger N, Irion K ve De Vreese C. (2016) Shrinking core? Exploring the differential agenda setting power of traditional and personalized news media, info, Vol. 18, Issue: 6, 26-41.
  • Mostafa J (2002) Information Customization. Intelligent Systems, IEEE, 17(6), 8–11.
  • Negroponte N (1995) Being Digital, Knopf Doubleday Publishing Group, New York
  • Obendorf H, Harald W, Eelco H ve Matthias M (2007) Web Page Revisitation Revisited: Implications of a Long-Term Click-Stream Study of Browser Usage, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 597–606.
  • Pariser E (2011) The Filter Bubble: What the Internet is Hiding From You. New York, Penguin.
  • Pons A (2013) Beyond deliberation and cyber-balkanization, Master Thesis, Erasmus University Rotterdam
  • Putnam R D (2000). Bowling alone: The collapse and revival of American community, New York, Simon & Schuster
  • Rainie L (2009) The new news audience, http://www.pewinternet.org/2009/11/13/the-new-news-audience/, erişim tarihi: 22.06.2017
  • Rimer B K ve Kreuter M W (2006) Advancing tailored health communication: A persuasion and message effects perspective, Journal of Communication, 56, 184-201.
  • Roberto A J, Krieger J L ve Beam M A (2009) Enhancing web-based prevention messages for Hispanics using targeting and tailoring, Journal of Health Communication, 14, 525-540.
  • Suhay E.,  Blackwell A,  Roche C, Bruggeman L (2015) Forging Bonds and Burning Bridges: Polarization and Incivility in Blog Discussions About Occupy Wall Street, American Politics Research, Vol. 43(4), 643–679.
  • Sundar S S ve Marathe S S (2010) Personalization versus Customization: The Importance of Agency, Privacy, and Power Usage, Human Communication Research, 36, 298–322.
  • Sunstein C (2001) Republic.com 2.0. Princeton, NJ: Princeton University Press.
  • Sunstein C (2004) Democracy and Filtering, December 2014, Vol. 47, No.12, 57-59.
  • Sunstein C (2009) Republic.com 2.0. Princeton, NJ: Princeton University Press.
  • VanAlstyne M ve Brynjolffson E (2005) Global village or cyber-balkans? Modeling and measuring the integration of electronic communities, Management Science, 51, 851–868.
  • Van Cuilenburg J ve McQuail D (2003) Media policy paradigm shifts: Towards a new communications policy paradigm, European Journal of Communication, 18, 181–207.
  • Van Dijk J (2016) Ağ Toplumu, Özlem Sakin (çev), Kafka, İstanbul.
  • Vesanen J (2007) What is personalization? A conceptual framework. European Journal of Marketing, 41, 409-418.
  • Vydiswaran V G V ve Chandrasekar R (2010) Improving the Online News Experience, HCIR’10, August 22, New Brunswick, NJ, USA, 1-4.
  • Wind J ve Rangaswamy A (2001) Customerization: The Next Revolution in Mass Customization, Journal of Interactive Marketing, 15, 13-32.
  • Zheng L, Li L, Hong W, Li T (2013) PENETRATE: Personalized news recommendation using ensemble hierarchical clustering, Expert Systems with Applications 40, 2127–2136.
Toplam 43 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Araştırma Makaleleri
Yazarlar

Bilge Narin

Yayımlanma Tarihi 11 Temmuz 2018
Gönderilme Tarihi 28 Eylül 2017
Yayımlandığı Sayı Yıl 2018 Cilt: 11 Sayı: 2

Kaynak Göster

APA Narin, B. (2018). Kişiselleştirilmiş Çevrimiçi Haber Akışının Yankı Odası Etkisi, Filtre Balonu ve Siberbalkanizasyon Kavramları Çerçevesinde İncelenmesi. Selçuk İletişim, 11(2), 232-251. https://doi.org/10.18094/josc.340471

Cited By