Echoes in the Digital Abyss: Examining the Bubble Surrounding Security and Privacy Discourse in Social Networks
Reagan Dennison, Saanvi Sharma, Noshir Contractor, Sruti Bhagavatula
Abstract
The dissemination of security and privacy education and guidance has been and still remains a challenge today. Social networks represent a potential avenue for sharing best practices, and experimentally they have been found to be effective at this task. While this appears promising, in the real world, security and privacy discussions would need to reach a wide range of people to be effective, avoiding the "interest bubbles" that commonly occur. We sought to understand how the communities surrounding security and privacy discourse operate, with a focus on what challenges need to be overcome to enable security and privacy discourse and advice to reach a wider audience. Indeed, we found that in-the-wild security and privacy discussions in social networks portray quite a different picture than in experimental settings. We built and analyzed the structure of a graph containing over 13 million users on the "X" platform (formerly "Twitter"), including 10,159 users who posted about security and privacy and their followers. Prior work has shown that users are more likely to consider information within social media if their like-minded social ties have visibly engaged with it. Our findings indicate that the users generating or participating in security discussions largely already belong to highly clustered technology and security- and privacy-related interest communities, which suggests that the people who are not already in the "inner circle" of relevant interests are likely not exposed effectively to these discussions. We conclude with reflections and ideas on increasing the reach of security and privacy guidance in social networks.
Create a lesson
Related papers
Prepared Or Unprepared? Evaluating Healthcare Workforce Readiness for Clinical Adoption of Artificial Intelligence in Nigeria
Abbas M. Rabiu, Abdulrazaq A. Zubair, Um-mulkhairi Ibrahim et al.
Could Underwater Data Centers Pose a Risk to AI Treaty Verification?
James Teague, Ashmita Rajmohan, Yannick Muehlhaeuser
Control-Theoretic Content Moderation
Benedetta Tessa, Serena Tardelli, Marco Avvenuti et al.
"If I Had to Buy Just ONE: Galaxy S26 Ultra": Auditing AI-Generated Product Recommendations
Lucas G. Uberti-Bona Marin, Thales Bertaglia, Giovanni Astante et al.
Understanding AI Provider Recommendations in Local Service Markets
Hazem Ibrahim, Yasir Zaki
Toward a Time-Aware Assessment Framework for the Carbon Cost of AI-Enabled Decarbonization
Chenrui Xu, Burcu Akinci, Christopher McComb