KİŞİSELLEŞTİRİLMİŞ ÇEVRİMİÇİ HABER AKIŞININ YANKI ODASI ETKİSİ, FİLTRE BALONU VE SİBERBALKANİZASYON KAVRAMLARI ÇERÇEVESİNDE İNCELENMESİ

Bu araştırmanın amacı hem kişiselleştirmiş çevrimiçi haber kavramını ve türlerini açıklamakhem de yeni medyanın ayırt edici bu özelliğine yönelik farklı görüşleri literatürtaraması ile serimleyerek bütüncül bir bakış açısı sağlamaktır. Bu kapsamda, çalışmadaöncelikle kişiselleştirilmiş haber içerikleri sunan algoritmaların temel çalışma mantığıüzerinde durulmuştur. Ardından kişisel haber akışlarının otomatik oluşturulmasınayönelik eleştirel çalışmaların varsayımları yankı odası etkisi, filtre balonu vesiberbalkanizasyon kavramları bağlamında tartışılmıştır. Son olarak, bu araştırmalardakieleştirileri iddialı bulan deneysel çalışmaların sonuçları sunularak; literatürdeki farklıyaklaşımların karşılaştırılması sağlanmıştır. Çalışmada ayrıca kişiselleştirilmiş haberlerinneden olabileceği sorunlardan korunmak için geliştirilen teknolojik araçlar da açıklanmıştır.Araştırmanın sonunda, gazetecilik etiğinin medya sahiplik yapısı ve içeriğeyönelik kodların yanı sıra kişiselleştirilmiş haber akışı gibi teknolojik süreçlerin şeffaflığınıda içerecek şekilde geliştirilmesi gerektiği vurgulanarak; dijital medya okuryazarlığıderslerinin bu konuları da kapsaması önerilmiştir.

THE EXAMINATION OF PERSONALIZED NEWS FEED IN THE CONTEXT OF ECHO CHAMBER EFFECT, FILTER BUBBLE AND CYBERBALCANIZATION CONCEPTS

This research aims to explain the concept and types of personalized online news feeds, as well as to provide a holistic view by presenting various arguments on this distinctive feature of the new media with literature review. In this context, the study firstly focuses on the fundamental 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.

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  • 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.
  • 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.
  • Brainard L A (2009) Cyber-Communities. İçinde H.K. Anheier ve S. Toepler (Eds.), International Encyclopedia of Civil Society, New York, NY: Springer Science & Business Media, 587–600.
  • Chen C, Meng X, Xu Z, ve Lukasiewicz T (2017) Location-Aware Personalized News Recommendation With Deep Semantic Analysis, IEEE, 2169-3536.
  • Choi Y J ve Lee J H (2013) Cross-Cutting Effects of Hypertext Navigation on the Convergence of Attitudes, Mass Communication and Society, 16: 369–390.
  • Chung C ve Fu K (2017) The Relationship Between Cyberbalkanization and Opinion Polarization: Time-Series Analysis on Facebook Pages and Opinion Polls During the Hong Kong Occupy Movement and the Associated Debate on Political Reform, Journal of Computer-Mediated Communication 22, 266–283.
  • Colleoni E, Rozza, A ve 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.
  • 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 ve 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, 1-204.
  • 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-under researched-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 ve Hullman J (2015) Designing for Personalized Article Content, Computation + Journalism (C+J), 1-5.
  • 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-politicalbubble.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.
  • Lassen D D (2005) The Effect of Information on Voter Turnout: Evidence from a Natural Experiment, American Journal of Political Science, 49: 103–118.
  • Liao Q V ve Fu W T (2014) Can You Hear Me Now? Mitigating the Echo Chamber Effect by Source Position Indicators, CSCW, February 15-19, 2014, Baltimore, MD, USA 184-196.
  • Maccatrozzo V (2012) Burst the Filter Bubble: Using Semantic Web to Enable Serendipity, 11th International Semantic Web Conference Boston, MA, USA, November 11-15, 2012 Proceedings, Part II, Heidelberg, Springer, 391-398.
  • 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 No. 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
  • Nguyen T T, Hui P M, Harper F M, Terveen L ve Kontsan W J A (2014) Exploring the Filter Bubble: The Effect of Using Recommender Systems on Content Diversity, WW’14, April 7–11, 2014, Seoul, Korea.
  • 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.
  • Powers E (2017) My News Feed Is Filtered? Awareness of News Personalization Among College Students, Digital Journalism, February, 1-21.
  • 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.
  • Resnick P, Garret R K, Kriplean T, Munson S A ve Stroud N J (2013) Bursting Your (Filter) Bubble: Strategies for Promoting Diverse, Exposure CSCW ’13 Companion, Feb. 23–27, 2013, San Antonio, Texas, USA, 95-100.
  • 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 ve 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, Princeton, NJ: Princeton University Press. Sunstein C (2004) Democracy and Filtering, December 2014, Vol. 47, No.12, 57-59.
  • Turow J (2013) The Daily You: How the New Advertising Industry Is Defining Your Identity and Your Worth, Yale University Press, New Haven, London.
  • Vaidhyanathan S (2011) The Googlization of Everything: (And Why We Should Worry), University of California Press, Berkeley, Los Angeles.
  • Van Alstyne M ve Brynjolfsson E (1996) Electronic Communities: Global Villages or Cyberbalkanization? (Best Theme Paper), ACM; Special Interest Group on Management Information Systems in Proceedıngs Of The Internatıonal Conference On Informatıon Systems, 80-98.
  • Van Alstyne M ve Brynjolffson E (2005) Global village or cyber-balkans? Modeling and measuring the integration of electronic communities, Management Science, 51, 851–868.
  • 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.
  • Williams D (2007) The Impact of Time Online: Social Capital and Cyberbalkanization, Cyberpsychology & Behavior, Volume 10, Number 3, 398- 406.
  • Wind J ve Rangaswamy A (2001) Customerization: The Next Revolution in Mass Customization, Journal of Interactive Marketing, 15, 13-32.
  • Woo-young C (2008) The Cyber Balkanization and Structural Transformation of the Public Sphere in Korea, Journal of Contemporary Eastern Asia, Volume 7, No.2: 29-48.
  • Zheng L, Li L, Hong W ve Li T (2013) PENETRATE: Personalized news recommendation using ensemble hierarchical clustering, Expert Systems with Applications 40, 2127–2136.
Selçuk İletişim-Cover
  • Yayın Aralığı: Yılda 2 Sayı
  • Başlangıç: 1999
  • Yayıncı: Selçuk Üniversitesi İletişim Fakültesi