Social Cybersecurity: Social Influence and Design in End-User Cybersecurity
summary
Analyzes 1.5 million Facebook users’ networks to measure adoption of three tools: login notifications, login approvals (Facebook 2FA), and trusted contacts. Finds social influence drives behavior but standard tools show negative effect at low exposure consistent with disaffiliation, while trusted contacts spreads positively. Runs a 50,000 randomized experiment on social proof cues and reports a best condition with ~36% higher click-through and roughly 10% more five‑month adoptions for promoted security tools. Design levers: observability, cooperation, stewardship.
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chapters (6)
- 0:00Start
- 0:09Social Cybersecurity: Social Influence and Design In End-User Cybersecurity
- 5:37Absent knowledge of how social influences affect security behaviors we have little hope of doing better.
- 17:47How can we design systems that encourage better cybersecurity behaviors?
- 19:02How can we design cooperate Security systems that make group security a joint effort
- 20:17How can we design systems that allo people to act on their concern fo the security of their oved on?
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