Computer-Mediated Communication Social Privacy in a Networked World

Cheshire & King - CMC i216 Fall 2016 Quick Review Personal disclosure is a fundamental human activity Disclosure in CMCs is a reflection of this activity What looks like a “Privacy Paradox” can be unpacked into more nuance that contextualizes disclosure Disclosure is motivated by: Different aspects of privacy (psych, social, info) The need/desire to build social capital Lack of privacy “literacy” (people are unaware of info gathering by CMC platforms, or they don’t care) On Tuesday we talked about why people disclose; two primary theories of privacy that inform research in this area; the privacy paradox and how behavior that is characterized as paradoxical can be explained with more nuance. 9/22/16 Cheshire & King - CMC i216 Fall 2016

Today: Implications of Disclosure Social Consequences Turbulence: interpersonal consequences, such as embarrassment, loss of friendship, loss of privacy Objective harms: loss of job, discrimination, reputational harms http://www.forbes.com/sites/kashmirhill/2009/12/10/either-mark-zuckerberg-got-a-whole-lot-less-private-or-facebooks-ceo-doesnt-understand-the-companys-new-privacy-settings/#7f3f4b721c61 9/22/16 Cheshire & King - CMC i216 Fall 2016

What’s happening on the ground? All sorts of social malfeasance occurring from what people disclose publicly. Here’s one of the early examples: would that happen today? Why: Context collapse, (mis)imagined audience, poor grasp of privacy controls? 9/22/16 Cheshire & King - CMC i216 Fall 2016

Info harvesting/reuse/predictions Jernigan & Mistree’s 2009 Gaydar study It’s not just what you make explicit, it’s also what you can infer Other examples of inferences (correct or not)? Walk through the four studies assigned today; each one presents a different aspect of the conflicts we observe between disclosure and privacy in CMC spaces (all but one are focused on FB, sorry) http://immediatefuture.co.uk/blog/new-software-can-predict-personality-traits-what-does-your-facebook-profile-say-about-you/ 9/22/16 Cheshire & King - CMC i216 Fall 2016

Cheshire & King - CMC i216 Fall 2016 Circa 2010 9/22/16 Cheshire & King - CMC i216 Fall 2016

Cheshire & King - CMC i216 Fall 2016 Here’s a recent example from our reading. This is an interesting case of the marriage of data (likely your phone number) + your social relationships (friend graph) 9/22/16 Cheshire & King - CMC i216 Fall 2016

Michal Kosinski et al. PNAS 2013;110:5802-5805 Prediction accuracy of classification for dichotomous/dichotomized attributes expressed by the AUC. This is a slide from another study, more recent than Gaydar (2013), that used FB profile info to predict certain profile attributes from (public data? Check!) Prediction accuracy of classification for dichotomous/dichotomized attributes expressed by the AUC. Michal Kosinski et al. PNAS 2013;110:5802-5805 Private traits and attributes are predictable from digital records of human behavior 9/22/16 Cheshire & King - CMC i216 Fall 2016 ©2013 by National Academy of Sciences

Cheshire & King - CMC i216 Fall 2016 Turn an Email Address into a Social Profile. When all you have is an email address, Flowtown can give you a name, age, gender, occupation, location and all the social networks that person is on. This is a now defunct example of a commercial service that was harvesting SNS profile information for ad purposes – not necessarily above board. 9/22/16 Cheshire & King - CMC i216 Fall 2016

User Misunderstandings How come I’m allowing strangers to go through my phone? Key finding: people didn’t entirely grasp what apps were, unaware of smartphone architecture, didn’t realize the extent to which data could be shared unaware 9/22/16 Cheshire & King - CMC i216 Fall 2016

Cheshire & King - CMC i216 Fall 2016 Privacy: Is there an app for that? Similarly, we found that people didn’t understand what Facebook apps were, that they weren’t part of FB, that they had access to profile and their social graph, and that by adding apps they were in effect exposing their friends. 9/22/16 Cheshire & King - CMC i216 Fall 2016

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Silent Listeners (Stutzman et al.) Facebook users over time became more privacy seeking by progressively limiting data shared publicly with strangers Facebook’s 2009 changes reversed this amount of info users revealed to connected friends increased, as well as to third party apps; often occurred w/o explicit consent or awareness; the network remains an “imagined” community that does not map to actual audiences Included this one because it’s one of the only longitudinal studies out there on privacy, and our perceptions of our information privacy over time is an area that many of us are curious about 9/22/16 Cheshire & King - CMC i216 Fall 2016

Cheshire & King - CMC i216 Fall 2016 Facebook privacy settings circa Dec 2009 9/22/16 Cheshire & King - CMC i216 Fall 2016

Cheshire & King - CMC i216 Fall 2016 Facebook privacy settings circa July 2010 9/22/16 Cheshire & King - CMC i216 Fall 2016

Cheshire & King - CMC i216 Fall 2016 http://mattmckeon.com/facebook-privacy/ 9/22/16 Cheshire & King - CMC i216 Fall 2016

Cheshire & King - CMC i216 Fall 2016 http://mattmckeon.com/facebook-privacy/ 9/22/16 Cheshire & King - CMC i216 Fall 2016

Cheshire & King - CMC i216 Fall 2016 http://mattmckeon.com/facebook-privacy/ 9/22/16 Cheshire & King - CMC i216 Fall 2016

Cheshire & King - CMC i216 Fall 2016 http://mattmckeon.com/facebook-privacy/ 9/22/16 Cheshire & King - CMC i216 Fall 2016

Implications of “Silent Listeners” How much is our expectation of privacy bound to the platform we are using? “Power of the environment in affecting individual choices: the entity that controls the structure . . . Ultimately remains able to affect how actors make choices in that environment.” Privacy by overexposure? How much of this study is just specific to FB? Riyana & Bret 9/22/16 Cheshire & King - CMC i216 Fall 2016

Cheshire & King - CMC i216 Fall 2016 Boundary Management Litt & Hargittai’s paper Incorporates the work of Sandra Petronio (using an updated version of Altman’s theory: Communication Privacy Management) Privacy == individuals’ information boundary (rule) management w/r/t others Turbulence == breakdown in expectations when personal info goes beyond a person’s desired boundaries 9/22/16 Cheshire & King - CMC i216 Fall 2016

Cheshire & King - CMC i216 Fall 2016 Key findings Skill is a key concern in Hargittai’s work – found those with more Internet skills less likely to experience negative outcomes Self monitoring: “ability & motivation to pick up on social cues and modify their self-presentations” Higher self-monitoring skills & privacy behaviors == more turbulence Context collapse, or perceived vs. actual privacy misaligned, also control paradox Higher self monitors might be more sensitive, more aware negatives exist, better at ID’ing it, not necessarily more likely to experience Prior negative experiences may also contribute While we can cause our own turbulence, more often generated by what others share about us – how do we design for this? Privacy literacy: skills still independent of one’s experience of turbulence Andrew commented on this portion Eszter has a new article focusing on youth, skills, and the privacy paradox: participants were apathetic because they felt there was a loss of control, privacy violations were inevitable, no opt out Privacy as a group process in CMC, not as only an individual responsibility 9/22/16 Cheshire & King - CMC i216 Fall 2016

Misplaced Confidences – Control Paradox Individuals’ perceived control over release and access of private info increases willingness to disclose Questions assumptions about rational, informed choice Part of a larger body of research by Acquisti questioning decision-making models; role of heuristics Posits that privacy preferences are contextual and subject to manipulation This is one of their most important papers – it questions the heart of the entire model of notice and choice Return to Bret’s comment about privacy incoherence 9/22/16 Cheshire & King - CMC i216 Fall 2016

Cheshire & King - CMC i216 Fall 2016 Design solutions? Better (re)designed privacy controls Privacy “nudges” Predictive privacy preferences Incorporating longitudinal aspects How do we design for social privacy? 9/22/16 Cheshire & King - CMC i216 Fall 2016

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