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Applying contextual integrity to the study of social network sites

Authors: Hutton, Luke;

Applying contextual integrity to the study of social network sites

Abstract

Social network sites (SNSs) have become very popular, with more than 1.39 billion people using Facebook alone. The ability to share large amounts of personal information with these services, such as location traces, photos, and messages, has raised a number of privacy concerns. The popularity of these services has enabled new research directions, allowing researchers to collect large amounts of data from SNSs to gain insight into how people share information, and to identify and resolve issues with such services. There are challenges to conducting such research responsibly, ensuring studies are ethical and protect the privacy of participants, while ensuring research outputs are sustainable and can be reproduced in the future. These challenges motivate the application of a theoretical framework that can be used to understand, identify, and mitigate the privacy impacts of emerging SNSs, and the conduct of ethical SNS studies. In this thesis, we apply Nissenbaum's model of contextual integrity to the study of SNSs. We develop an architecture for conducting privacy-preserving and reproducible SNS studies that upholds the contextual integrity of participants. We apply the architecture to the study of informed consent to show that contextual integrity can be leveraged to improve the acquisition of consent in such studies. We then use contextual integrity to diagnose potential privacy violations in an emerging form of SNS.

Country
United Kingdom
Related Organizations
Keywords

Social network sites, Ethics, Facebook, HM742.H8, Software architecture, Contextual integrity, 303, Reproducibility, Social media, Privacy, Online social networks--Research, Online social networks--Research--Moral and ethical aspects

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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