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As part of a Youth Advisory Board of teens (YAB), a longitudinal and interactive program to engage with teens for adolescent online safety research, we used an Asynchronous Remote Community (ARC) method with seven teens to explore their social media usage and perspectives on privacy on social media. There was a spectrum of privacy levels in our teen participants’ preferred social media platforms and preferences varied depending on their user goals such as content viewing and socializing. They recognized privacy risks they could encounter on social media, hence, actively used privacy features afforded by platforms to stay safe while meeting their goals. In addition, our teen participants designed solutions that can aid users to exercise more granular control over determining what information on their accounts is to be shared with which groups of users. Our findings highlight the need to ensure researchers and social media developers work with teens to provide teen-centric solutions for safer experiences on social media.
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This content will become publicly available on April 1, 2026
Can Social Media Privacy and Safety Features Protect Targets of Interpersonal Attacks? A Systematic Analysis
Social media applications have benefited users in several ways, including ease of communication and quick access to information. However, they have also introduced several privacy and safety risks. These risks are particularly concerning in the context of interpersonal attacks, which are carried out by abusive friends, family members, intimate partners, co-workers, or even strangers. Evidence shows interpersonal attackers regularly exploit social media platforms to harass and spy on their targets. To help protect targets from such attacks, social media platforms have introduced several privacy and safety features. However, it is unclear how effective they are against interpersonal threats. In this work, we analyzed ten popular social media applications, identifying 100 unique privacy and safety features that provide controls across eight categories: discoverability, visibility, saving and sharing, interaction, self-censorship, content moderation, transparency, and reporting. We simulated 59 different attack actions by a persistent attacker — aimed at account discovery, information gathering, non-consensual sharing, and harassment — and found many were successful. Based on our findings, we proposed improvements to mitigate these risks.
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- Award ID(s):
- 2339679
- PAR ID:
- 10589576
- Publisher / Repository:
- Proceedings on Privacy Enhancing Technologies Symposium
- Date Published:
- Journal Name:
- Proceedings on Privacy Enhancing Technologies
- Volume:
- 2025
- Issue:
- 2
- ISSN:
- 2299-0984
- Page Range / eLocation ID:
- 326 to 343
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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