TY - GEN
T1 - Online Privacy Heuristics that Predict Information Disclosure
AU - Sundar, S. Shyam
AU - Kim, Jinyoung
AU - Rosson, Mary Beth
AU - Molina, Maria D.
N1 - Funding Information:
This research is supported by the U. S. National Science Foundation (NSF) via Standard Grant No. CNS-1450500.
Publisher Copyright:
© 2020 ACM.
PY - 2020/4/21
Y1 - 2020/4/21
N2 - Online users' attitudes toward privacy are context-dependent. Studies show that contextual cues are quite influential in motivating users to disclose personal information. Increasingly, these cues are embedded in the interface, but the mechanisms of their effects (e.g., unprofessional design contributing to more disclosure) are not fully understood. We posit that each cue triggers a specific "cognitive heuristic" that provides a rationale for decision-making. Using a national survey (N = 786) that elicited participants' disclosure intentions in common online scenarios, we identify 12 distinct heuristics relevant to privacy, and demonstrate that they are systematically associated with information disclosure. Data show that those with a higher accessibility to a given heuristic are more likely to disclose information. Design implications for protection of online privacy and security are discussed.
AB - Online users' attitudes toward privacy are context-dependent. Studies show that contextual cues are quite influential in motivating users to disclose personal information. Increasingly, these cues are embedded in the interface, but the mechanisms of their effects (e.g., unprofessional design contributing to more disclosure) are not fully understood. We posit that each cue triggers a specific "cognitive heuristic" that provides a rationale for decision-making. Using a national survey (N = 786) that elicited participants' disclosure intentions in common online scenarios, we identify 12 distinct heuristics relevant to privacy, and demonstrate that they are systematically associated with information disclosure. Data show that those with a higher accessibility to a given heuristic are more likely to disclose information. Design implications for protection of online privacy and security are discussed.
UR - http://www.scopus.com/inward/record.url?scp=85091306263&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85091306263&partnerID=8YFLogxK
U2 - 10.1145/3313831.3376854
DO - 10.1145/3313831.3376854
M3 - Conference contribution
AN - SCOPUS:85091306263
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
T2 - 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020
Y2 - 25 April 2020 through 30 April 2020
ER -