SOSYAL AĞLARDA VERİ GİZLİLİĞİ: TÜRKİYE’DE WHATSAPP GİZLİLİK SÖZLEŞMESİNE GÖSTERİLEN TEPKİLERİNİN DUYGU ANALİZİ

Öz

Sosyal ağlarda kullanıcıların en önemli endişelerinden biri kişisel bilgilerin farklı kurum veya kurumlarla paylaşılması yani veri gizliliği ihlalidir. Türkiye’de sosyal medyada veri gizliliği, WhatsApp’ın gizlilik sözleşmesini güncellenmesinin duyurulmasıyla tartışmaların odağına yerleşmiştir. Bu araştırmada 10-12 Ocak 2021 tarihlerinde Twitter’da Trend Topics olan #watsappsiliyoruz etiketi ile paylaşılan tweetlerin Metin Madenciliği yöntemleri ile analiz edilmesi amaçlanmıştır. Duygu analizi sonucunda tweetlerin yaklaşık %60’ının olumlu, %30’unun ise olumsuz olduğu görülmüştür. Yapısal olarak olumlu olmasına rağmen "anlık" ve "TC" ifadelerinin genel olarak mizahi içeriklerde, "peki" kelimesinin Whatsapp ve diğer uygulamaların güvenliliğinin sorgulanmasında ve "gelin" kelimesinin farklı uygulamalara geçilmesi konusunda çağrı ifadesi olarak kullanıldığı görülmüştür. Pozitif ve negatif paylaşımlarında ortak kullanılan kelimelere ait kelime bulutu analizi sonucunda, alternatif uygulamalar olan Bip, Telegram kelimeleri ile gizlilik endişelerini ifade eden "sildim", "geri", "kabul" kelimeleri ön plandadır. Bu sonuçlar; kullanıcıların sosyal ağlardan vazgeçmelerinin hayli zor olduğu, ancak gizlilik endişelerini giderecek farklı sosyal ağların veya uygulamaların ortaya çıkmasının gerekli olduğunu göstermektedir.

Anahtar Kelimeler

• Veri gizliliği
• duygu analizi
• kelime bulutu

DATA PRIVACY ON SOCIAL NETWORKS: SENTIMENT ANALYSIS ON REACTIONS IN TURKEY TO WHATSAPP’S CONFIDENTIALITY AGREEMENT

Öz

One of the most important concerns of users on social networks is that their personal data may be shared with different organizations, which is a breach of data privacy. Data privacy on social media became the focus of discussions in Turkey as it was announced that WhatsApp’s confidentiality agreement was updated. This research aimed to analyze the tweets posted with the hashtag #watsappsiliyoruz (We're deleting WhatsApp), which became Trend Topics on Twitter on January 10-12, 2021. Sentiment analysis showed that out of these tweets, 60% was positive, and 30% was negative. It was seen that although they were structurally positive, the phrases "anlık (instant) " and "TC (abbreviation for the Republic of Turkey) " was used in humorous contents; the word "peki (alright) " was used to question the reliability of WhatsApp and other similar applications; and the word "gelin (come) " was used as a call to move into different applications. A cloud of words analysis on the words used commonly in positive and negative posts showed that the words Bip and Telegram, which are the alternative applications, and the words "sildim (I’ve deleted)", "geri (back)" and "kabul (agree)" were the most common ones. These results suggest that it is significantly hard for users to give up on social networks, but it is necessary that different social networks or applications should appear, which would ease these concerns about data privacy.

Anahtar Kelimeler

• Data privacy
• sentiment analysis
• word clouds

Kaynakça

1. Akgün, A.C., Paltun, D., & Abanoz, M. (2021). Süperpanoptik iktidar: Whatsapp Türkiye gizlilik ilkesi uygulaması örneği özelinde bir inceleme. Ege Üniversitesi İletişim Fakültesi Yeni Düşünceler Hakemli E-Dergisi, (15), 78-95.
2. Almuhimedi, H., Schaub, F., Sadeh, N., Adjerid, I., Acquisti, A., Gluck, J., Cranor, L.F., & Agarwal, Y. (2015). Your location has been shared 5,398 times!: A field study on mobile app privacy nudging. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (ss. 787–796). New York: ACM.
3. Antonakaki, D., Fragopoulou, P., & Ioannidis, S. (2021). A survey of Twitter research: Data model, graph structure, sentiment analysis and attacks. Expert Systems with Applications, 164, 114006, 1-25.
4. Baruh, L., Secinti, E. & Cemalcilar, Z. (2017). Online privacy concerns and privacy management: A meta-analytical review. Journal of Communication, 67(1), 26-53. Beresford, A. R., Kübler, D., & Preibusch, S. (2012), Unwillingness to pay for privacy: A field experiment. Economics Letters, 117(1), 25-27.
5. Bélanger, F., Hiller, J. S., & Smith, W. J. (2002). Trustworthiness in electronic commerce: The role of privacy, security, and site attributes. Journal of Strategic Information Systems, 11, 245-270.
6. Bhardwaj, V. & Rana, A. (2021). WhatsApp privacy policy in ındia – Infringement of fundamental right to informational privacy., JURIST – Professional Commentary, February 4, 2021, https://www.jurist.org/commentary/2021/02/bhardwaj-rana-WhatsApp-policy-india/.,
7. Bleier, A., Goldfarb, A., & Tuckerc, C. (2020). Consumer privacy and the future of data-based innovation and marketing. International Journal of Research in Marketing. 1-15.
8. Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication & Society, 15(5), 662–679.

9. Brown, A. J. (2020). Should ı stay or should ı leave?: Exploring (dis)continued Facebook use after the Cambridge Analytica scandal. Social Media + Society, 6(1), 1-8.
10. Cadwalladr, C., & Graham-Harrison, E. (2018). Revealed: 50 million Facebook profiles harvested for Cambridge Analytica in major data breach, 8 Şubat 2022 tarihinde https://www.theguardian.com/news/2018/mar/17/cambridge-analytica-facebook-influence-us-election adresinden erişildi.
11. Culnan, M. J., & Armstrong, P. K. (1999). Information privacy concerns, procedural fairness and impersonal trust: An empirical investigation. Organization Science, 10(1), 104-115.
12. Çubukçu, C. & Aktürk, C. (2021). University students’ privacy concerns towards social media platforms: Whatsapp contract change. Veri Bilimi, 4(2), 72-79.
13. Demirtas, E., & Pechenizkiy, M. (2013). Cross-lingual polarity detection with machine translation. Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining (1-8).
14. Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. 11 Şubat 2022 tarihinde https://arxiv.org/abs/1810.04805 adresinden erişildi.
15. Fersini, E. (2017). Sentiment analysis in social networks: A machine learning perspective, F.A. Pozzi, E. Fersini, E. Messina & B. Liu, B. (Eds), Sentiment Analysis in Social Networks içinde (ss. 91–111). Morgan Kaufmann.
16. Gomez, J., Pinnick, T., & Soltani, A. (2009). Know privacy: The current state of web privacy, data collection, and information sharing. School of Information, University of California Berkeley.
17. Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT press.
18. Gülpınar Demirci, V. (2021). Dijital pazarlamada veri analitiği ve iş zekası. M. Sağlam (Ed.) Dijitalleşen Dünyada Pazarlama içinde. (ss. 273-296), Ankara: Nobel Yayıncılık.
19. Hayran, A., & Sert, M. (2017). Sentiment analysis on microblog data based on word embedding and fusion techniques. 25th Signal Processing and Communications Applications Conference (SIU) (ss. 1-4). IEEE.
20. Hsu, T. (2018, March 21). For many users a “last straw” that led them to quit. New York Times. 14 Kasım 2021 tarihinde https://www.nytimes.com/2018/03/21/technology/users-abandon-facebook.html adresinden erişildi.
21. Jianqiang, Z., Xiaolin, G., & Xuejun, Z. (2018). Deep convolution neural networks for Twitter sentiment analysis. IEEE Access, 6, 23253-23260.
22. John, M., Koch, S., Heimerl, F., Müller, A., Ertl, T., & Kuhn, J. (2015). Interactive visual analysis of german poetics. Digital Humanities.
23. John, M., Marbach, E., Lohmann, S., Heimerl, F., & Ertl, T. (2018). MultiCloud: Interactive word cloud visualization for multiple texts. Proceeding of Graphical Interface, 25-32.
24. Lapowsky, I. (2018, April 4). Facebook exposed 87 million users to Cambridge Analytica. Wired. 10 Kasım 2021 tarihinde https://www.wired.com/story/facebook-exposed-87-million-users-to-cambridge-analytica/ adresinden erişilmiştir.
25. Marwick, A. E., & Boyd, D. (2014). Networked privacy: How teenagers negotiate context in social media. New Media & Society, 16(7), 1051–1067.
26. Metheny, M. (2017). Federal cloud computing: The definitive guide for cloud service providers, Second Edition, Elsevier Inc, Syngress.
27. Naseem, U., Razzak, I., Musial, K., & Imran, M. (2020). Transformer based deep intelligent contextual embedding for Twitter sentiment analysis. Future Generation Computer Systems, 113, 58-69.
28. Oomen, I., & Leenes, R. (2008), Privacy risk perceptions and privacy protection strategies. Leeuw, E., Fischer-Hübner, S., Tseng, J. and Borking, J. (Eds) de Policies and research in identity management içinde (ss. 121-138). Springer US.
29. Pavlou, P. A. (2011). State of the information privacy literature: Where are we now and where should we go? MIS Quarterly, 35(4), 977–988.
30. Pota, M., Ventura, M., Catelli, R., & Esposito, M. (2021). An effective BERT-based pipeline for Twitter sentiment analysis: A case study in Italian. Sensors, 21(1), 1-21.
31. Qiu, X., Sun, T., Xu, Y., Shao, Y., Dai, N., & Huang, X. (2020). Pre-trained models for natural language processing: A survey. Science China Technological Sciences, 63(10), 1872-1897.
32. Rekabet Kurulu (2021). 2 Kasım 2021 tarihinde https://www.rekabet.gov.tr/tr/Guncel/rekabet-kurulu-facebook-ve-WhatsApp-hakk-14728ae4f653eb11812700505694b4c6 adresinden erişildi.
33. Smith, H. J. Dinev, T., & Xu, H. (2011). Information privacy research: An interdisciplinary review, MIS Quarterly, 35(4), 989-1015.
34. Taddicken, M. (2013). The “privacy paradox” in the social web: The impact of privacy concerns, individual characteristics, and the perceived social relevance on different forms of self-disclosure. Journal of Computer-Mediated Communication, 19(2), 248–273.
35. Turancı, E. (2021). Dijital dünyada kişisel veri ve etik: Gizlilik politikası bağlamında “#whatsappsiliyoruz” krizinde kullanıcı tepkilerini anlamak. TRT Akademi, 6(12) , 272-295. Ulukan, G. (2021). 11 günde WhatsApp, Telegram ve BiP'in kullanıcı sayılarının değişimi. 11 Ekim 2021 tarihinde https://webrazzi.com/2021/01/14/11-gunde-whatsapp-telegram-ve-bip-in-kullanici-sayilarinin-degisimi/ adresinden erişildi.
36. Wang, L., Miao, D., & Zhang, Z. (2014). Emotional analysis on text sentences based on topics. Computer Science, 41(3), 32-35.
37. We Are Social (2021). Digital 2021: The Latest Insights Into The ‘State Of Digital’ Reports. 2 Kasım 2021 tarihinde https://wearesocial.com/uk/blog/2021/01/digital-2021-the-latest-insights-into-the-state-of-digital/ adresinden erişildi. Westin, A.F. (1967). Privacy and freedom. New York: Atheneum.
38. Wijoyo, H., Limakrisna, N., & Suryanti, S. (2021). The effect of renewal privacy policy WhatsApp to customer behavior. Insight Management Journal, 1(2), 26-31.
39. Wu, P. F., Vitak, J., & Zimmer, M. T. (2019). A contextual approach to information privacy research. Journal of the Association for Information Science and Technology. 1-6.
40. Yu, J. (2021). Discovering Twitter through computational social science methods, Universitat Autònoma de Barcelona 11 Şubat 2022 tarihinde https://www.tdx.cat/handle/10803/671609#page=1 adresinden erişildi.
41. Zafeiropoulou, A. M., Millard, D. E., Webber, C., & O'Hara, K. (2013). Unpicking the privacy paradox: Can structuration theory help to explain location-based privacy decisions? Proceedings of the 5th Annual ACM Web Science Conference, May 2-4, Paris, France.
42. Zimbra, D., Abbasi, A., Zeng, D., & Chen, H. (2018). The state-of-the-art in Twitter sentiment analysis: A review and benchmark evaluation. ACM Transactions on Management Information Systems (TMIS), 9(2), 1-29.