"I Didn't Sign Up for This!": Informed Consent in Social Network Research
By Luke Hutton, H. Tristan. 2015
49 citations recorded by the source corpus.
The issue of whether, and how, to obtain informed consent for researchstudies that use social network data has recently come to the fore insome controversial cases.Determining how to acquire valid consent that meets the expectations of participants, while minimising the burden placed on them, remains an open problem.We apply Nissenbaum's model of contextual integrity to the consent process, to study whether social norms of willingness to share social network data can be leveraged to avoid burdening participants with too many interventions, while still accurately capturing their own sharing intent. We find that for the 27.7% of our participants (N = 109) who conform to social norms, contextual integrity can be used to significantly reduce the time taken to capture their consent, while still maintaining accuracy. Our findings have implications for researchers conducting such studies who are looking to acquire informed consent without having to burden participants with many interactions.
Subfields: Communication, Sociology and Political Science
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Communication
- Alexandra Olteanu
- Fernando Diaz
- Carlos Castillo
- Emre Kıcıman
- Emre Kiciman
- Muhammad Imran
- Gabriella Kazai
- Ricardo A. Baeza-Yates
In Sociology and Political Science
- Alexandra Olteanu
- Fernando Diaz
- Carlos Castillo
- Emre Kıcıman
- Emre Kiciman
- Gabriella Kazai
- Ricardo A. Baeza-Yates
- Muhammad Imran
Citations in the corpus
- Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “Studies that leverage data from millions of social media users often do it without any kind of consent from them (Zimmer, 2010; Hutton and Henderson, 2015a).”
- A Critical Review of Online Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2018, background): “In the last part, we will cover ethical caveats when leveraging social data such as discriminatory treatment as a result of algorithmic reinforcement of human prejudice [3], lack of explicit user consent [18, 37], user manipulation (see Facebook’s contagion experiment [21]), identity disclosure [7],”