The Labor of Fun: Understanding the Social Relationships between Gamers and Paid Gaming Teammates in China

Title of the Paper

The Labor of Fun: Understanding the Social Relationships between Gamers and Paid Gaming Teammates in China

Bibliographic Information

• Research Domain: Game Studies, Human-Computer Interaction, Sharing Economy
• Keywords: Gamers, Social Media, Online Communities, Sharing Economy, Virtual Relationships, Self-Presentation

Research Background and Problem Statement

• Identified Issues or Challenges:

  • Matchmaking functions in online games are typically based on technical evaluations, failing to meet players' social needs (e.g., personality compatibility).
  • Players find it difficult to establish lasting, genuine friendships within games.
  • Anonymous social platforms pose trust issues.
  • A new platform model—paid teammate matchmaking platforms—has emerged in China, but there is a lack of research on why players use these platforms and how they impact players' social experiences.

• Significance:

  • Understanding how emerging sharing economy platforms (e.g., Bixin) meet players' social needs can help improve social mechanisms in games and drive the development of related technologies and services.

• Research Motivation and Related Work:

  • Studies on user motivations, trust mechanisms, and social relationships in the sharing economy provide the theoretical foundation for this paper.
  • This research extends the study of social relationships in gaming, particularly the interactions between paid teammates and regular players.

Proposed Solution

• Methods and Solutions Proposed:

  • Investigate the social relationships between paid teammates and regular players through interviews with players and paid teammates.
  • Focus on players' motivations for hiring paid teammates, platform mechanism design, and user behavior patterns.
  • Explore the characteristics of the paid teammate economy and its similarities and differences with traditional sharing economies.

• Innovations:

  • Introduced a framework for paid teammates as a new form of sharing economy, emphasizing the importance of social interaction in this economy.
  • Examined how paid services influence users' virtual world social relationships and self-presentation.
  • Introduced an analysis of cross-platform, mixed-reality (between gaming and real life) interaction models.

• Implementation Steps and Key Techniques:

  • Conducted interviews with 16 paid teammates on the Chinese platform Bixin to analyze player motivations, interaction forms, and challenges.
  • Employed qualitative research methods, including participatory observation and semantic coding.

Research Findings

• Specific Findings:

  • The primary motivations for hiring paid teammates include social needs, satisfaction from gaming progress, and the cultural context of "face" in China.
  • Paid teammates attract players by designing personal profiles (e.g., "avatars" and "voices") and use layered communication strategies to maintain client relationships.
  • Paid teammates represent a new form of sharing economy, significantly different from traditional platforms like Airbnb and Uber.

• Advantages:

  • The platform provides higher-quality social matchmaking, reducing the "toxic behavior" often associated with random matchmaking.
  • The platform fulfills deeper entertainment and social interaction needs.

• Experimental and Evaluation Results:

  • Voice is proven to be a key factor in attracting players; players are more inclined to hire teammates with friendly voices rather than just those with strong gaming skills.
  • Despite the popularity of paid teammate systems, trust and authenticity issues remain prominent, such as fake profiles.

• Limitations and Future Directions:

  • Limitations: The platform cannot effectively regulate in-game experiences or arbitrate disputes; the prevalence of fake profiles is difficult to address.
  • Future Directions:
    1. Design stronger trust verification mechanisms, such as identity authentication or game account binding.
    2. Develop new recommendation and matchmaking algorithms to enhance user experience.
    3. Explore the expansion of "experiential" services in cross-domain sharing economies.

This paper provides a comprehensive and in-depth analysis of the paid teammate sharing economy in China, while also contributing supplementary research on user relationships and dynamics within the sharing economy. It offers significant insights for the study of human-computer interaction and the design of social platforms.