Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

When Nobody Around Is Real: Exploring Public Opinions and User Experiences On the Multi-Agent AI Social Platform

Qiufang Yu, Mengmeng Wu, Xingyu Lan

TL;DR

The paper investigates public opinion and lived experience on a multi-agent AI social platform, Social.AI, to understand how AI-dominated sociality reshapes social interaction. It employs a two-stage approach: a public-comment content analysis (n=883) to assess broad attitudes and risks, and a 7-day diary study with 20 participants to capture first-hand experiences and expectation projection. Findings show public discourse emphasizes macro risks such as illusory sociality and internet death, while diary data reveal nuanced expectation projection, with both positive and negative experiences including rapid feedback and cognitive load, homogenized responses, and shallow emotional connections. The work argues for a rethinking of design and theory to account for AI as a dominant medium of sociality, offering guidelines on agent diversity, attention pacing, and reciprocal social dynamics to foster healthier AI-driven social ecosystems.

Abstract

Powered by large language models, a new genre of multi-agent social platforms has emerged. Apps such as Social.AI deploy numerous AI agents that emulate human behavior, creating unprecedented bot-centric social networks. Yet, existing research has predominantly focused on one-on-one chatbots, leaving multi-agent AI platforms underexplored. To bridge this gap, we took Social.AI as a case study and performed a two-stage investigation: (i) content analysis of 883 user comments; (ii) a 7-day diary study with 20 participants to document their firsthand platform experiences. While public discourse expressed greater skepticism, the diary study found that users did project a range of social expectations onto the AI agents. While some user expectations were met, the AI-dominant social environment introduces distinct problems, such as attention overload and homogenized interaction. These tensions signal a future where AI functions not merely as a tool or an anthropomorphized actor, but as the dominant medium of sociality itself-a paradigm shift that foregrounds new forms of architected social life.

When Nobody Around Is Real: Exploring Public Opinions and User Experiences On the Multi-Agent AI Social Platform

TL;DR

The paper investigates public opinion and lived experience on a multi-agent AI social platform, Social.AI, to understand how AI-dominated sociality reshapes social interaction. It employs a two-stage approach: a public-comment content analysis (n=883) to assess broad attitudes and risks, and a 7-day diary study with 20 participants to capture first-hand experiences and expectation projection. Findings show public discourse emphasizes macro risks such as illusory sociality and internet death, while diary data reveal nuanced expectation projection, with both positive and negative experiences including rapid feedback and cognitive load, homogenized responses, and shallow emotional connections. The work argues for a rethinking of design and theory to account for AI as a dominant medium of sociality, offering guidelines on agent diversity, attention pacing, and reciprocal social dynamics to foster healthier AI-driven social ecosystems.

Abstract

Powered by large language models, a new genre of multi-agent social platforms has emerged. Apps such as Social.AI deploy numerous AI agents that emulate human behavior, creating unprecedented bot-centric social networks. Yet, existing research has predominantly focused on one-on-one chatbots, leaving multi-agent AI platforms underexplored. To bridge this gap, we took Social.AI as a case study and performed a two-stage investigation: (i) content analysis of 883 user comments; (ii) a 7-day diary study with 20 participants to document their firsthand platform experiences. While public discourse expressed greater skepticism, the diary study found that users did project a range of social expectations onto the AI agents. While some user expectations were met, the AI-dominant social environment introduces distinct problems, such as attention overload and homogenized interaction. These tensions signal a future where AI functions not merely as a tool or an anthropomorphized actor, but as the dominant medium of sociality itself-a paradigm shift that foregrounds new forms of architected social life.
Paper Structure (49 sections, 1 figure, 8 tables)

This paper contains 49 sections, 1 figure, 8 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. CASA and Anthropomorphic Chatbots
  4. Multi-Agent AI Systems
  5. Influence of AI on Social Media
  6. Study 1: Comment Analysis
  7. Data Collection
  8. Coding
  9. Findings
  10. Attitudes
  11. Motivations
  12. Emotional Motivations
  13. Functional Motivations
  14. Perceived Social Support
  15. Social Empowerment
  16. ...and 34 more sections

Figures (1)

  • Figure 1: A typical user interaction flow on Social.AI: customizing follower types (left), publishing a post (middle), and receiving automated responses from AI agents (right).