SOSYAL MEDYA PERSPEKTİFİNDEN BÜYÜK VERİ: FACEBOOK VAKA ÇALIŞMASI

Sosyal medya platformları internet biliminin gelişmesi ve bilgisayarların bir iletişim aracı olarak kişiler, kurumlar ve toplulukları bir araya getirebilme yetisi sayesinde sadece bir iletişim aracı olarak kullanılmasının ötesine geçerek kurumların algı yönetimi ve manipülasyon araçları haline gelmiştir. Dijital iletişim araçlarından yararlanılarak hedef kullanıcıların belirlenmesi ve stratejilerin oluşturulması için kullanıcı verileri kullanılmıştır. Bulunduğumuz çağ itibariyle veri kavramı her geçen gün önemini göstermektedir. The Economist'in "Dünyanın en değerli kaynağı artık petrol değil, veridir" isimli makalesi de veri kavramının çarpıcı bir noktaya ulaştığını gösteriyor. Kullanıcı bilgilerinden yola çıkarak kullanıcı profil, davranış ve alışkanlıklarının tespit edilmesi süreci ise kümülatif artan devasa veri yığınlarının olduğu bir sonuç ortaya çıkarmaktadır. Bu devasa veri yığınlarına ‘Big Data’ ismi verilmektedir. Big Data için güncel, her kesimden kullanıcıyı kapsayan ve devasa veri yığınlarını elde etmek için sosyal medya araçları kullanılmaktadır. Çalışmada büyük verinin sosyal medya platformlarındaki rolü tartışılmaktadır. Büyük veri ve sosyal medya kavramları ve bunların gelişim süreçleri, büyük verinin avantaj ve dezavantajları ile veri ihlallerinden bahsedilerek Facebook platformu aracılığıyla veri ihlalleri incelenecektir. Çalışma, veri ihlalleri ve büyük verinin sınırları hakkında bir tartışma noktası oluşturmayı amaçlamaktadır.

BIG DATA FROM SOCIAL MEDIA PERSPECTIVE: A CASE STUDY WITH FACEBOOK

Thanks to the development of internet science and the ability of computers to bring individuals, institutions, and communities together as a communication tool, social media platforms have gone beyond being used as a communication tool and have become perception management and manipulation tools of institutions. Using digital communication tools, user data was used to identify target users and create strategies. In the current age, the concept of data shows its importance frequently. The Economist's article "The world's most valuable resource is no longer oil, but data" shows that the concept of data has reached a striking point. The process of determining user profiles, behaviours and habits based on user information takes place thanks to cumulatively increasing huge data stacks. These massive stacks of data are called ‘Big Data’. For Big Data, social media tools are used to obtain up-to-date, huge data stacks covering users from all walks of life. The role of big data in social media platforms is discussed in the study. The concepts of big data and social media and their development processes, the advantages and disadvantages of big data and data breaches will be discussed, and data breaches will be examined through the Facebook platform. The study aims to create a discussion point about data breaches and the limits of big data.

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  • Aran, Ali. 2020. “Here’s What Happens Every Minute on the Internet in 2020.” Retrieved December 27, 2020 (https://www.visualcapitalist.com/every-minute-internet-2020/).
  • Benjamin, Ruha. 2019a. “Assessing Risk, Automating Racism: A Health Care Algorithm Reflects Underlying Racial Bias in Society.” Science 366(6464):421–22.
  • Benjamin, Ruha. 2019b. Race after Technology: Abolitionist Tools for the New Jim Code. Medford: Polity Press.
  • Boyd, Danah, and Kate Crawford. 2012. “Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon.” Information Communication and Society 15(5):662–79.
  • Bronson, N., Lento, T., & Wiener, J. L. 2015. “Open data challenges at Facebook.” 2015 IEEE 31st International Conference on Data Engineering. Seoul, Korea (South) : IEEE.
  • Brown, A. P. 2008. “A review of the literature on case study research.” Canadian Journal for New Scholars in Education, 1-13.
  • Caliskan, Aylin, Joanna J. Bryson, and Arvind Narayanan. 2017. “Semantics Derived Automatically from Language Corpora Contain Human-like Biases.” Science 356(6334):183–86.
  • Clarke, Laurie. 2020. “How the Cambridge Analytica Scandal Unravelled.” Retrieved December 29, 2020 (https://www.newstatesman.com/science-tech/social-media/2020/10/how-cambridge-analytica-scandal-unravelled).
  • Chmiliar, L. 2012. “Multiple-Case Designs. Encyclopedia of Case Study Researc” (s. 582-583). içinde Thousand Oaks: SAGE Publications.
  • Coté, Mark. 2014. “Data Motility: The Materiality of Big Social Data.” Cultural Studies Review 20(1):121–49.
  • Cukier, Kenneth, and Viktor Mayer-Schoenberger. 2014. Datafication in Big Data.
  • Curran, Dylan. 2018. “Are You Ready? Here Is All the Data Facebook and Google Have on You.” The Guardian. Retrieved December 29, 2020 (https://www.theguardian.com/commentisfree/2018/mar/28/all-the-data-facebook-google-has-on-you-privacy).
  • Fuller, M. 2019. “Article Big data and the Facebook scandal: Issues and responses.” Theology, 14-21.
  • Gutta, Surya. 2020. “Data Science: The 5 V’s of Big Data.” Retrieved December 28, 2020 (https://suryagutta.medium.com/the-5-vs-of-big-data-2758bfcc51d).
  • Hancock, R. D., & Algozzine, B. 2006. “Doing case study research.” New York: Teachers College Press.
  • Henriksen, E. E. 2019. “Big data, microtargeting, and governmentality in cyber-times. The case of the Facebook-Cambridge Analytica data scandal.” Oslo, Norway: University of Oslo.
  • Hewage, T. N., Halgamuge, M. N., Syed, A., & Ekici, G. 2018. “Review: Big Data Techniques of Google, Amazon, Facebook and Twitter.” Journal of Communications, 94-100.
  • Jougleux , P. 2022. “Personal Data and Privacy Protection: Facebook and the Big Data Mountain.” Facebook and the (EU) Law: How the Social Network Reshaped the Legal Framework (s. 13-92). içinde Springer.
  • Mahrt, Merja, and Michael Scharkow. 2013. “The Value of Big Data in Digital Media Research.” Journal of Broadcasting and Electronic Media 57(1):20–33.
  • Mazur, Elizabeth. 2010. “Collecting Data from Social Networking Web Sites and Blogs.” Pp. 77–90 in Advanced methods for conducting online behavioral research. American Psychological Association.
  • Metcalf , J., & Crawford, K. 2016. “Where are human subjects in Big Data research? The emerging ethics divide.” Big Data & Society, 1-14.
  • Microsoft. 2013. “The Big Bang: How the Big Data Explosion Is Changing the World - Stories.” Retrieved December 27, 2020 (https://news.microsoft.com/2013/02/11/the-big-bang-how-the-big-data-explosion-is-changing-the-world/).
  • Nabi, Robin, and Mary Oliver. 2009. The SAGE Handbook of Media Processes and Effects. Los Angeles; London: SAGE.
  • Panger, G. 2016. “Reassessing the Facebook experiment: critical thinking about the validity of Big Data research.” Information, Communication & Society, 19(8), 1108-1126.
  • Prescott, Bonnie. 2016. “Better Together: Artificial Intelligence Approach Improves Accuracy in Breast Cancer Diagnosis.” Retrieved December 28, 2020 (https://hms.harvard.edu/news/better-together).
  • Quenqua, Douglas. 2015. “Facebook Knows You Better Than Anyone Else.” Retrieved (https://www.nytimes.com/2015/01/20/science/facebook-knows-you-better-than-anyone-else.html).
  • Statista. 2020. “Most Popular Social Networks Worldwide as of October 2020, Ranked by Number of Active Users.” Retrieved December 28, 2020 (https://www.statista.com/statistics/272014/global-social-networks-ranked-by-number-of-users/).
  • The Economist. 2017. “The World’s Most Valuable Resource Is No Longer Oil, but Data.” Retrieved December 28, 2020 (https://www.economist.com/leaders/2017/05/06/the-worlds-most-valuable-resource-is-no-longer-oil-but-data).
  • van Dijck, José. 2014. “Datafication, Dataism and Dataveillance: Big Data between Scientific Paradigm and Ideology.” Surveillance and Society 12(2):197–208.
  • Vincos. 2020. “World Map of Social Networks.” Retrieved December 29, 2020 (https://vincos.it/world-map-of-social-networks/).
  • Wallach, Omri. 2020. “Mapped: Facebook’s Path to Social Network Domination (2008-2020).” Retrieved December 29, 2020 (https://www.visualcapitalist.com/map-facebook-path-social-network-domination/).
  • Ward, Jonathan Stuart, and Adam Barker. 2013. “Undefined By Data: A Survey of Big Data Definitions.”
  • Weerkamp, W., and M. de Rijke. 2012. “Activity Prediction: A Twitter-Based Exploration” edited by Information and Language Processing Syst. SIGIR 2012 Workshop on Time-Aware Information Access: #TAIA2012. Accepted Papers.
  • Williams, Betsy Anne, Catherine F. Brooks, and Yotam Shmargad. 2018. “How Algorithms Discriminate Based on Data They Lack: Challenges, Solutions, and Policy Implications.” Journal of Information Policy 8:78–115.
  • Zikopoulos, Paul C., Chris Eaton, Dirk deRoos, Thomas Deutsch, and George Lapis. 2012. Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. edited by S. Sit. The McGraw-Hill Companies.