Authors
Jeffrey Warshaw, Tara Matthews, Steve Whittaker, Chris Kau, Mateo Bengualid, Barton A Smith
Publication date
2015/4/18
Book
Proceedings of the 33rd annual ACM conference on human factors in computing systems
Pages
797-806
Description
Recent research has developed analytics that threaten online self-presentation and privacy by automatically generating profiles of individuals' most personal traits-their personality, values, motivations, and so on. But we know little about people's reactions to personal traits profiles of themselves, or what influences their decisions to share such profiles. We present an early qualitative study of people's reactions to a working hyper-personal analytics system. The system lets them see their personality and values profile derived from their own social media text. Our results reveal a paradox. Participants found their personal traits profiles creepily accurate and did not like sharing them in many situations. However, they felt pressured by the social risks of not sharing and showed signs of learned helplessness, leading them to share despite their misgivings. Further, they felt unqualified to significantly modify their profile …
Total citations
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Scholar articles
J Warshaw, T Matthews, S Whittaker, C Kau… - Proceedings of the 33rd annual ACM conference on …, 2015