Honey Trap or Romantic Utopia: A Case Study of Final Fantasy XIV Players PII Disclosure in Intimate Partner-Seeking Posts

2025-03-12

AI Summary

This study investigates sensitive personally identifiable information (PII) disclosure behaviors and associated privacy/security risks among players of massively multiplayer online games (MMOGs)—specifically *Final Fantasy XIV* (FFXIV)—when posting friendship-seeking posts on real-world social platforms such as Weibo. Applying a mixed-methods approach combining LDA topic modeling and qualitative thematic analysis, the authors coded 1,288 such posts. They systematically identify five distinct PII disclosure patterns and four types of expectation misalignment, revealing cross-platform identity management challenges that heighten risks of privacy leakage and emotional exploitation. The study innovatively proposes a socio-technical design framework for virtual-world social safety that balances intimate relationship formation with privacy preservation. It yields seven actionable, implementation-ready design recommendations. Grounded in empirical evidence, this work advances digital intimacy governance in MMOG contexts by bridging theory, user behavior, and practical intervention.

Technology Category

• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Application Domains: Humanities & Computational Social Science
• Machine Learning: Privacy

Application Category

• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Security and Privacy: Data transparency and provenance
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

Abstract

Massively multiplayer online games (MMOGs) can foster social interaction and relationship formation, but they pose specific privacy and safety challenges, especially in the context of mediating intimate interpersonal connections. To explore the potential risks, we conducted a case study on Final Fantasy XIV (FFXIV) players intimate partner seeking posts on social media. We analyzed 1,288 posts from a public Weibo account using Latent Dirichlet Allocation (LDA) topic modeling and thematic analysis. Our findings reveal that players disclose sensitive personal information and share vulnerabilities to establish trust but face difficulties in managing identity and privacy across multiple platforms. We also found that players expectations regarding intimate partner are diversified, and mismatch of expectations may leads to issues like privacy leakage or emotional exploitation. Based on our findings, we propose design implications for reducing privacy and safety risks and fostering healthier social interactions in virtual worlds.

Problem

• Explores privacy risks in MMOGs for intimate relationships.
• Analyzes PII disclosure in FFXIV players' partner-seeking posts.
• Proposes design solutions to mitigate privacy and safety risks.

Innovation

• Latent Dirichlet Allocation topic modeling
• Thematic analysis of social media posts
• Design implications for privacy safety