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Charnsethikul, Pithayuth; Zunquti, Almajd; Lucas, Gale; Mirkovic, Jelena
Navigating Social Media Privacy: Awareness, Preferences, and Discoverability Journal Article
In: PoPETs, vol. 2025, no. 4, pp. 620–638, 2025, ISSN: 2299-0984.
@article{charnsethikul_navigating_2025,
title = {Navigating Social Media Privacy: Awareness, Preferences, and Discoverability},
author = {Pithayuth Charnsethikul and Almajd Zunquti and Gale Lucas and Jelena Mirkovic},
url = {https://petsymposium.org/popets/2025/popets-2025-0148.php},
doi = {10.56553/popets-2025-0148},
issn = {2299-0984},
year = {2025},
date = {2025-10-01},
urldate = {2025-08-19},
journal = {PoPETs},
volume = {2025},
number = {4},
pages = {620–638},
abstract = {Social media platforms provide various privacy settings, which users can adjust to fit their privacy needs. Platforms claim that this is sufficient – users have power to accept the default settings they like, and change those they do not like. In this paper, we seek to quantify user awareness of, preferences around and ability to adjust social media privacy settings. We conduct an online survey of 541 participants across six different social media platforms: Facebook, Instagram, X, LinkedIn, TikTok, and Snapchat. We focus on nine privacy settings that are commonly available across these platforms, and evaluate participants’ preferences for privacy, awareness of the privacy settings and ability to locate them. We find that default settings are ill-aligned with user preferences – 92% of participants prefer at least one of the privacy options to be more private than the default. We further find that users are generally not aware of privacy settings, and struggle to find them. 80% of participants have never seen at least one privacy setting, and 79% of participants rated at least one setting as hard to find. We also find that the fewer privacy settings a user has seen, the harder for them to locate those settings, and the higher the level of privacy they desire. Additionally, we find that there are significant differences in privacy setting preferences and usability across different user age groups and across platforms. Older users are more conservative about their privacy, they have seen significantly fewer privacy settings, and they spend significantly more time locating them than younger users. On some platforms, like LinkedIn, users opt for higher visibility, while on others they prefer more privacy. Some platforms, like TikTok, make it significantly easier for users to locate privacy settings. Based on our findings, we provide recommendations on default values and how to improve usability of privacy settings on social media.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Gurney, Nikolos; Miller, John H.; Pynadath, David V.
Exploring the choice landscape: Anchoring and framing effects on search behavior in complex choices Journal Article
In: Journal of Choice Modelling, vol. 55, pp. 100549, 2025, ISSN: 17555345.
@article{gurney_exploring_2025,
title = {Exploring the choice landscape: Anchoring and framing effects on search behavior in complex choices},
author = {Nikolos Gurney and John H. Miller and David V. Pynadath},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1755534525000120},
doi = {10.1016/j.jocm.2025.100549},
issn = {17555345},
year = {2025},
date = {2025-06-01},
urldate = {2025-04-15},
journal = {Journal of Choice Modelling},
volume = {55},
pages = {100549},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Brun, Antonin; Lucas, Gale; Becerik-Gerber, Burçin
Under Pressure: Contextualizing Workplace Stress Towards User-Centered Interventions Proceedings Article
In: Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, pp. 1–9, ACM, Yokohama Japan, 2025, ISBN: 979-8-4007-1395-8.
@inproceedings{brun_under_2025,
title = {Under Pressure: Contextualizing Workplace Stress Towards User-Centered Interventions},
author = {Antonin Brun and Gale Lucas and Burçin Becerik-Gerber},
url = {https://dl.acm.org/doi/10.1145/3706599.3719987},
doi = {10.1145/3706599.3719987},
isbn = {979-8-4007-1395-8},
year = {2025},
date = {2025-04-01},
urldate = {2025-06-12},
booktitle = {Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems},
pages = {1–9},
publisher = {ACM},
address = {Yokohama Japan},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Tran, Minh; Chang, Di; Siniukov, Maksim; Soleymani, Mohammad
DIM: Dyadic Interaction Modeling for Social Behavior Generation Book Section
In: Leonardis, Aleš; Ricci, Elisa; Roth, Stefan; Russakovsky, Olga; Sattler, Torsten; Varol, Gül (Ed.): Computer Vision – ECCV 2024, vol. 15095, pp. 484–503, Springer Nature Switzerland, Cham, 2024, ISBN: 978-3-031-72912-6 978-3-031-72913-3, (Series Title: Lecture Notes in Computer Science).
@incollection{leonardis_dim_2024,
title = {DIM: Dyadic Interaction Modeling for Social Behavior Generation},
author = {Minh Tran and Di Chang and Maksim Siniukov and Mohammad Soleymani},
editor = {Aleš Leonardis and Elisa Ricci and Stefan Roth and Olga Russakovsky and Torsten Sattler and Gül Varol},
url = {https://link.springer.com/10.1007/978-3-031-72913-3_27},
doi = {10.1007/978-3-031-72913-3_27},
isbn = {978-3-031-72912-6 978-3-031-72913-3},
year = {2024},
date = {2024-12-01},
urldate = {2025-01-16},
booktitle = {Computer Vision – ECCV 2024},
volume = {15095},
pages = {484–503},
publisher = {Springer Nature Switzerland},
address = {Cham},
note = {Series Title: Lecture Notes in Computer Science},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
Filter
2025
Charnsethikul, Pithayuth; Zunquti, Almajd; Lucas, Gale; Mirkovic, Jelena
Navigating Social Media Privacy: Awareness, Preferences, and Discoverability Journal Article
In: PoPETs, vol. 2025, no. 4, pp. 620–638, 2025, ISSN: 2299-0984.
Abstract | Links | BibTeX | Tags: DTIC, Social
@article{charnsethikul_navigating_2025,
title = {Navigating Social Media Privacy: Awareness, Preferences, and Discoverability},
author = {Pithayuth Charnsethikul and Almajd Zunquti and Gale Lucas and Jelena Mirkovic},
url = {https://petsymposium.org/popets/2025/popets-2025-0148.php},
doi = {10.56553/popets-2025-0148},
issn = {2299-0984},
year = {2025},
date = {2025-10-01},
urldate = {2025-08-19},
journal = {PoPETs},
volume = {2025},
number = {4},
pages = {620–638},
abstract = {Social media platforms provide various privacy settings, which users can adjust to fit their privacy needs. Platforms claim that this is sufficient – users have power to accept the default settings they like, and change those they do not like. In this paper, we seek to quantify user awareness of, preferences around and ability to adjust social media privacy settings. We conduct an online survey of 541 participants across six different social media platforms: Facebook, Instagram, X, LinkedIn, TikTok, and Snapchat. We focus on nine privacy settings that are commonly available across these platforms, and evaluate participants’ preferences for privacy, awareness of the privacy settings and ability to locate them. We find that default settings are ill-aligned with user preferences – 92% of participants prefer at least one of the privacy options to be more private than the default. We further find that users are generally not aware of privacy settings, and struggle to find them. 80% of participants have never seen at least one privacy setting, and 79% of participants rated at least one setting as hard to find. We also find that the fewer privacy settings a user has seen, the harder for them to locate those settings, and the higher the level of privacy they desire. Additionally, we find that there are significant differences in privacy setting preferences and usability across different user age groups and across platforms. Older users are more conservative about their privacy, they have seen significantly fewer privacy settings, and they spend significantly more time locating them than younger users. On some platforms, like LinkedIn, users opt for higher visibility, while on others they prefer more privacy. Some platforms, like TikTok, make it significantly easier for users to locate privacy settings. Based on our findings, we provide recommendations on default values and how to improve usability of privacy settings on social media.},
keywords = {DTIC, Social},
pubstate = {published},
tppubtype = {article}
}
Gurney, Nikolos; Miller, John H.; Pynadath, David V.
Exploring the choice landscape: Anchoring and framing effects on search behavior in complex choices Journal Article
In: Journal of Choice Modelling, vol. 55, pp. 100549, 2025, ISSN: 17555345.
Links | BibTeX | Tags: DTIC, Social
@article{gurney_exploring_2025,
title = {Exploring the choice landscape: Anchoring and framing effects on search behavior in complex choices},
author = {Nikolos Gurney and John H. Miller and David V. Pynadath},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1755534525000120},
doi = {10.1016/j.jocm.2025.100549},
issn = {17555345},
year = {2025},
date = {2025-06-01},
urldate = {2025-04-15},
journal = {Journal of Choice Modelling},
volume = {55},
pages = {100549},
keywords = {DTIC, Social},
pubstate = {published},
tppubtype = {article}
}
Brun, Antonin; Lucas, Gale; Becerik-Gerber, Burçin
Under Pressure: Contextualizing Workplace Stress Towards User-Centered Interventions Proceedings Article
In: Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, pp. 1–9, ACM, Yokohama Japan, 2025, ISBN: 979-8-4007-1395-8.
@inproceedings{brun_under_2025,
title = {Under Pressure: Contextualizing Workplace Stress Towards User-Centered Interventions},
author = {Antonin Brun and Gale Lucas and Burçin Becerik-Gerber},
url = {https://dl.acm.org/doi/10.1145/3706599.3719987},
doi = {10.1145/3706599.3719987},
isbn = {979-8-4007-1395-8},
year = {2025},
date = {2025-04-01},
urldate = {2025-06-12},
booktitle = {Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems},
pages = {1–9},
publisher = {ACM},
address = {Yokohama Japan},
keywords = {Social},
pubstate = {published},
tppubtype = {inproceedings}
}
2024
Tran, Minh; Chang, Di; Siniukov, Maksim; Soleymani, Mohammad
DIM: Dyadic Interaction Modeling for Social Behavior Generation Book Section
In: Leonardis, Aleš; Ricci, Elisa; Roth, Stefan; Russakovsky, Olga; Sattler, Torsten; Varol, Gül (Ed.): Computer Vision – ECCV 2024, vol. 15095, pp. 484–503, Springer Nature Switzerland, Cham, 2024, ISBN: 978-3-031-72912-6 978-3-031-72913-3, (Series Title: Lecture Notes in Computer Science).
Links | BibTeX | Tags: DTIC, Social
@incollection{leonardis_dim_2024,
title = {DIM: Dyadic Interaction Modeling for Social Behavior Generation},
author = {Minh Tran and Di Chang and Maksim Siniukov and Mohammad Soleymani},
editor = {Aleš Leonardis and Elisa Ricci and Stefan Roth and Olga Russakovsky and Torsten Sattler and Gül Varol},
url = {https://link.springer.com/10.1007/978-3-031-72913-3_27},
doi = {10.1007/978-3-031-72913-3_27},
isbn = {978-3-031-72912-6 978-3-031-72913-3},
year = {2024},
date = {2024-12-01},
urldate = {2025-01-16},
booktitle = {Computer Vision – ECCV 2024},
volume = {15095},
pages = {484–503},
publisher = {Springer Nature Switzerland},
address = {Cham},
note = {Series Title: Lecture Notes in Computer Science},
keywords = {DTIC, Social},
pubstate = {published},
tppubtype = {incollection}
}