Modeling User Characteristics Associated with Interdependent Privacy Perceptions on Social Media

被引:4
作者
Amon, Mary Jean [1 ]
Necaise, Aaron [1 ]
Kartvelishvili, Nika [1 ]
Williams, Aneka [1 ]
Solihin, Yan [2 ]
Kapadia, Apu [3 ]
机构
[1] Univ Cent Florida, Sch Modeling Simulat & Training, 3100 Technol,Pkwy, Orlando, FL 32826 USA
[2] Univ Cent Florida, Dept Comp Sci, 4328 Scorpius St, Orlando, FL 32816 USA
[3] Indiana Univ, Luddy Sch Informat Comp & Engn, 700 N Woodlawn Ave, Bloomington, IN 47408 USA
基金
美国国家科学基金会;
关键词
Cluster analysis; dark triad; interdependent privacy; memes; sharing decisions; social media; DARK TRIAD; PERSONALITY-TRAITS; MULTIPARTY PRIVACY; BIG; 5; ONLINE; DISCLOSURE; NARCISSISM; BEHAVIORS; IMPULSIVITY; PREDICTORS;
D O I
10.1145/3577014
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
"Interdependent" privacy violations occur when users share private photos and information about other people in social media without permission. This research investigated user characteristics associated with interdependent privacy perceptions, by asking social media users to rate photo-based memes depicting strangers on the degree to which they were too private to share. Users also completed questionnaires measuring social media usage and personality. Separate groups rated the memes on shareability, valence, and entertainment value. Users were less likely to share memes that were rated as private, except when the meme was entertaining or when users exhibited dark triad characteristics. Users with dark triad characteristics demonstrated a heightened awareness of interdependent privacy and increased sharing of others' photos. A model is introduced that highlights user types and characteristics that correspond to different privacy preferences: privacy preservers, ignorers, and violators. We discuss how interventions to support interdependent privacy must effectively influence diverse users.
引用
收藏
页数:32
相关论文
共 123 条
  • [1] Allison P.D., 1999, MULTIPLE REGRESSION
  • [2] Looking through the Glass Ceiling: A Qualitative Study of STEM Women's Career Narratives
    Amon, Mary J.
    [J]. FRONTIERS IN PSYCHOLOGY, 2017, 8
  • [3] Influencing Photo Sharing Decisions on Social Media: A Case of Paradoxical Findings
    Amon, Mary Jean
    Hasan, Rakibul
    Hugenberg, Kurt
    Bertenthal, Bennett, I
    Kapadia, Apu
    [J]. 2020 IEEE SYMPOSIUM ON SECURITY AND PRIVACY (SP 2020), 2020, : 1350 - 1366
  • [4] The P Value and Statistical Significance: Misunderstandings, Explanations, Challenges, and Alternatives
    Andrade, Chittaranjan
    [J]. INDIAN JOURNAL OF PSYCHOLOGY MEDICINE, 2019, 41 (03): : 210 - 215
  • [5] Cyberbullying detection on twitter using Big Five and Dark Triad features
    Balakrishnan, Vimala
    Khan, Shahzaib
    Fernandez, Terence
    Arabnia, Hamid R.
    [J]. PERSONALITY AND INDIVIDUAL DIFFERENCES, 2019, 141 : 252 - 257
  • [6] Barnes Susan B., 2006, First Monday, V11, P1, DOI [doi:10.5210/fm.v11i9.1394, 10.5210/fm.v11i9.1394, DOI 10.5210/FM.V11I9.1394]
  • [7] Simplification of Privacy Disclosures: An Experimental Test
    Ben-Shahar, Omri
    Chilton, Adam
    [J]. JOURNAL OF LEGAL STUDIES, 2016, 45 : S41 - S67
  • [8] Besmer A, 2010, CHI2010: PROCEEDINGS OF THE 28TH ANNUAL CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, VOLS 1-4, P1563
  • [9] Generational differences in valuing usefulness, privacy and security negative experiences for paying for cloud services
    Bordonaba-Juste, M. Victoria
    Lucia-Palacios, Laura
    Perez-Lopez, Raul
    [J]. INFORMATION SYSTEMS AND E-BUSINESS MANAGEMENT, 2020, 18 (01) : 35 - 60
  • [10] boyd d., 2008, TAKEN OUT CONTEXT AM