Measuring the Emergence of Consent Management on the Web

Hils, Maximilian; Woods, Daniel; Böhme, Rainer

doi:10.1145/3419394.3423647

Cited by 51 publications

(62 citation statements)

References 44 publications

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“…They provide websites with a (customizable) cookie prompt to embed, store users' choices as browser cookies, and provide an API for advertisers to access this information. We refer to Hils et al [13,Fig. 2] for a visual depiction of the ecosystem.…”

Section: Transparency and Consent Framework (Tcf)mentioning

confidence: 99%

“…Web scraping studies have focused on implementation problems with TCF [64] or the ecosystem of consent management providers (CMP) [13]. These studies provide measurements of TCF in passing.…”

Section: Privacy Preferencesmentioning

confidence: 99%

“…Matte et al [8] show how TCF 1.x adoption varies by top-level domain (TLD) and identify the most popular CMPs across the top 1k sites in five EU country code TLDs. Hils et al [13] use longitudinal measurements to show the market growth of six CMPs, highlighting how fast the ecosystem changes.…”

Section: Privacy Preferencesmentioning

confidence: 99%

“…This work differs from existing work by focusing exclusively on the adoption of privacy preference signals. We largely ignore the actors [13,64] and interfaces [7,9,10] harvesting such signals and instead focus on which factors (e.g. website type, popularity, and partners) are associated with TCF adoption.…”

Section: Contributionmentioning

confidence: 99%

“…These laws prompted research that has largely focused on the interfaces through which optin [7][8][9][10] and opt-out [11,12] signals are collected. An ecosystem of actors has emerged to manage the collection of opt-in consent signals on behalf of websites [13]. Often these signals are collected and shared with a payfor-membership "Global Vendor List", which has been termed the "commodification of consent" [14].…”

Section: Introductionmentioning

confidence: 99%

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Privacy Preference Signals: Past, Present and Future

Hils

Woods

Böhme

2021

Proceedings on Privacy Enhancing Technologies

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Privacy preference signals are digital representations of how users want their personal data to be processed. Such signals must be adopted by both the sender (users) and intended recipients (data processors). Adoption represents a coordination problem that remains unsolved despite efforts dating back to the 1990s. Browsers implemented standards like the Platform for Privacy Preferences (P3P) and Do Not Track (DNT), but vendors profiting from personal data faced few incentives to receive and respect the expressed wishes of data subjects. In the wake of recent privacy laws, a coalition of AdTech firms published the Transparency and Consent Framework (TCF), which defines an optin consent signal. This paper integrates post-GDPR developments into the wider history of privacy preference signals. Our main contribution is a high-frequency longitudinal study describing how TCF signal gained dominance as of February 2021. We explore which factors correlate with adoption at the website level. Both the number of third parties on a website and the presence of Google Ads are associated with higher adoption of TCF. Further, we show that vendors acted as early adopters of TCF 2.0 and provide two case-studies describing how Consent Management Providers shifted existing customers to TCF 2.0. We sketch ways forward for a pro-privacy signal.

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Section: Transparency and Consent Framework (Tcf)mentioning

confidence: 99%

Section: Privacy Preferencesmentioning

confidence: 99%

Section: Privacy Preferencesmentioning

confidence: 99%

Section: Contributionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Privacy Preference Signals: Past, Present and Future

Hils

Woods

Böhme

2021

Proceedings on Privacy Enhancing Technologies

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A roadmap to achieving a healthier information ecosystem through GDPR implementation and privacy compliance technologies

Li,

Xiong,

Yang

2024

Asso for Info Science & Tech

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Privacy protection has become a central issue in information science, with the General Data Protection Regulation (GDPR) significantly impacting information ecosystems. Research gaps persist in understanding the causal relationship between GDPR implementation and websites' proactive changes, such as adopting privacy compliance technologies. This study aims to examine the influence of GDPR implementation on websites' information ecosystems and identify boundary conditions that may affect this relationship. Utilizing domain‐level data from a professional platform tracking website technologies before and after GDPR implementation, which encompasses a comprehensive longitudinal dataset of over 1.2 million websites, our results indicate that GDPR implementation has increased the decision, breadth, depth, and intensity of adopting related technologies. The variance in these adoptions is significantly shaped by the differing levels of institutional impacts experienced by trailblazing versus laggard industries. Our study contributes to the literature by revealing the importance of policy factors in fostering a healthier information ecosystem. We demonstrate the complex nature of the relationship between policy factors and technology adoption, highlighting the need for researchers to consider institutional context and industry‐specific characteristics. We further discuss valuable insights for relevant stakeholders.

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