Disagreeable Privacy Policies:  Mismatches between Meaning and Userss Understanding

Reidenberg, Joël R.; Breaux, Travis D.; Cranor, Lorrie Faith; French, Brian F.; Grannis, Amanda; Graves, James T.; Liu, Fei; McDonald, Aleecia M.; Norton, Thomas B.; Ramanath, Rohan; Russell, N. Cameron; Sadeh, Norman; Schaub, Florian

doi:10.2139/ssrn.2418297

Cited by 120 publications

(150 citation statements)

References 3 publications

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“…However, privacy policies, being long, complicated documents full of legal jargon, are sub-optimal for communicating information to individuals (Cranor, 2012;Cate, 2010;Reidenberg et al, 2015). Antón et al (2002) conducted a study in which they identified multiple privacy-related goals in accordance with Fair Information Practices, which included 'Choice/Consent' as one of the protection goals.…”

Section: Related Workmentioning

confidence: 99%

Identifying the Provision of Choices in Privacy Policy Text

Sathyendra

Wilson²,

Schaub

et al. 2017

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

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Websites' and mobile apps' privacy policies, written in natural language, tend to be long and difficult to understand. Information privacy revolves around the fundamental principle of notice and choice, namely the idea that users should be able to make informed decisions about what information about them can be collected and how it can be used. Internet users want control over their privacy, but their choices are often hidden in long and convoluted privacy policy documents. Moreover, little (if any) prior work has been done to detect the provision of choices in text. We address this challenge of enabling user choice by automatically identifying and extracting pertinent choice language in privacy policies. In particular, we present a two-stage architecture of classification models to identify opt-out choices in privacy policy text, labelling common varieties of choices with a mean F1 score of 0.735. Our techniques enable the creation of systems to help Internet users to learn about their choices, thereby effectuating notice and choice and improving Internet privacy.

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Section: Related Workmentioning

confidence: 99%

Identifying the Provision of Choices in Privacy Policy Text

Sathyendra

Wilson²,

Schaub

et al. 2017

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Indeed, the more specific the privacy policy (e.g., a policy that includes the type of information and how it is used), the less agreement consumers have in interpreting the notice, and the greater chance that the notice will be misunderstood by the average consumer (Reidenberg et al 2014); that is, respondents miss the nuances of the policy (Kelley et al 2010). When privacy expectations are highly dependent on contextual factors, such as the type of information and how it is used, consumers' judgments about privacy notices are typically broad and do not take the particular context into consideration.…”

Section: Factors That Influence Judgmentsmentioning

confidence: 99%

Privacy Notices as Tabula Rasa: An Empirical Investigation into how Complying with a Privacy Notice is Related to Meeting Privacy Expectations Online

Martin

2015

Journal of Public Policy & Marketing

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“…While research has highlighted the importance of allowing data legibility, negotiability and agency through control [32] to the users, there still remains an explicit call for the technological embodiment of these principles. Users are continued to be presented with incomprehensible privacy statements [31,37], followed by acceptance statements where the users are constrained to binary choices [45] dictated by service providers often leading to low levels of understanding and very little space to exercise control [43].…”

Section: Current Challengesmentioning

confidence: 99%

Explicating the Challenges of Providing Novel Media Experiences Driven by User Personal Data

Sailaja

Crabtree

McAuley

et al. 2018

Proceedings of the 2018 ACM International Conference on Interactive Experiences for TV and Online Video

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The turn towards personal data to drive novel media experiences has resulted in a shift in the priorities and challenges associated with media creation and dissemination. This paper takes up the challenge of explicating this novel and dynamic scenario through an interview study of employees delivering diverse personal data driven media services within a large U.K. based media organisation. The results identify a need for better interactions in the user-data-service ecosystem where trust and value are prioritised and balanced. Being legally compliant and going beyond just the mandatory to further ensure social accountability and ethical responsibility as an organisation are unpacked as methods to achieve this balance in data centric interactions. The work also presents how technology is seen and used as a solution for overcoming challenges and realising priorities to provide value while preserving trust within the personal data ecosystem.

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Disagreeable Privacy Policies: Mismatches between Meaning and Userss Understanding

Cited by 120 publications

References 3 publications

Identifying the Provision of Choices in Privacy Policy Text

Identifying the Provision of Choices in Privacy Policy Text

Privacy Notices as Tabula Rasa: An Empirical Investigation into how Complying with a Privacy Notice is Related to Meeting Privacy Expectations Online

Explicating the Challenges of Providing Novel Media Experiences Driven by User Personal Data

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