Privacy Lost in Online Education: Analysis of Web Tracking Evolution
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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Privacy Lost in Online Education : Analysis of Web Tracking Evolution. / Su, Zhan; Helles, Rasmus; Al-Laith, Ali Mohammed Ali; Veilahti, Antti Veikko Petteri; Saxena, Akrati; Simonsen, Jakob Grue.
Advanced Data Mining and Applications: 19th International Conference, ADMA 2023, Shenyang, China, August 21–23, 2023, Proceedings. red. / Xiaochun Yang; Heru Suhartanto; Guoren Wang; Bin Wang; Jing Jiang; Bing Li; Huaijie Zhu; Ningning Cui. Bind 2 Cham : Springer, Cham, 2023. s. 440-455 (Lecture Notes in Computer Science).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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TY - GEN
T1 - Privacy Lost in Online Education
T2 - Analysis of Web Tracking Evolution
AU - Su, Zhan
AU - Helles, Rasmus
AU - Al-Laith, Ali Mohammed Ali
AU - Veilahti, Antti Veikko Petteri
AU - Saxena, Akrati
AU - Simonsen, Jakob Grue
PY - 2023
Y1 - 2023
N2 - Digital tracking poses a significant and multifaceted threat to personal privacy and integrity. Tracking techniques, such as the use of cookies and scripts, are widespread on the World Wide Web and have become more pervasive in the past decade. This paper focuses on the historical analysis of tracking practices specifically on educational websites, which require particular attention due to their often mandatory usage by users, including young individuals who may not adequately assess privacy implications. The paper proposes a framework for comparing tracking activities on a specific domain of websites by contrasting a sample of these sites with a control group consisting of sites with comparable traffic levels, but without a specific functional purpose. This comparative analysis allows us to evaluate the distinctive evolution of tracking on educational platforms against a standard benchmark. Our findings reveal that although educational websites initially demonstrated lower levels of tracking, their growth rate from 2012 to 2021 has exceeded that of the control group, resulting in higher levels of tracking at present. Through our investigation into the expansion of various types of trackers, we suggest that the accelerated growth of tracking on educational websites is partly attributable to the increased use of interactive features, facilitated by third-party services that enable the collection of user data. The paper concludes by proposing ways in which web developers can safeguard their design choices to mitigate user exposure to tracking.
AB - Digital tracking poses a significant and multifaceted threat to personal privacy and integrity. Tracking techniques, such as the use of cookies and scripts, are widespread on the World Wide Web and have become more pervasive in the past decade. This paper focuses on the historical analysis of tracking practices specifically on educational websites, which require particular attention due to their often mandatory usage by users, including young individuals who may not adequately assess privacy implications. The paper proposes a framework for comparing tracking activities on a specific domain of websites by contrasting a sample of these sites with a control group consisting of sites with comparable traffic levels, but without a specific functional purpose. This comparative analysis allows us to evaluate the distinctive evolution of tracking on educational platforms against a standard benchmark. Our findings reveal that although educational websites initially demonstrated lower levels of tracking, their growth rate from 2012 to 2021 has exceeded that of the control group, resulting in higher levels of tracking at present. Through our investigation into the expansion of various types of trackers, we suggest that the accelerated growth of tracking on educational websites is partly attributable to the increased use of interactive features, facilitated by third-party services that enable the collection of user data. The paper concludes by proposing ways in which web developers can safeguard their design choices to mitigate user exposure to tracking.
U2 - 10.1007/978-3-031-46664-9_30
DO - 10.1007/978-3-031-46664-9_30
M3 - Article in proceedings
SN - 9783031466632
VL - 2
T3 - Lecture Notes in Computer Science
SP - 440
EP - 455
BT - Advanced Data Mining and Applications
A2 - Yang, Xiaochun
A2 - Suhartanto, Heru
A2 - Wang, Guoren
A2 - Wang, Bin
A2 - Jiang, Jing
A2 - Li, Bing
A2 - Zhu, Huaijie
A2 - Cui, Ningning
PB - Springer, Cham
CY - Cham
ER -
ID: 372622839