A large-scale analysis of public-facing, community-built chatbots on Character.AI

2025-05-19

AI Summary

This study addresses the lack of systematic empirical analysis of community-built AI characters on Character.AI. It presents the first large-scale analysis of 2.1 million English user-initiated greetings. Methodologically, it integrates web crawling, statistical language modeling, LDA topic modeling, and qualitative coding grounded in gender and power discourse frameworks. Three key findings emerge: (1) fandom distribution is highly skewed, with top intellectual properties dominating engagement; (2) cross-fandom interactions rely heavily on recurrent, script-like greeting templates; and (3) greetings systematically encode gendered power dynamics—e.g., feminized characters are disproportionately assigned submissive linguistic patterns. As the first large-scale empirical investigation of “public-facing social robots” in the generative AI era, this work extends theoretical foundations for human-AI interaction research and provides actionable, evidence-based insights for AI social safety governance.

Technology Category

• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Intelligent Robots: Embodied AI
• Application Domains: Humanities & Computational Social Science

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Web Mining and Content Analysis: Community question answering

Abstract

This paper presents the first large-scale analysis of public-facing chatbots on Character.AI, a rapidly growing social media platform where users create and interact with chatbots. Character.AI is distinctive in that it merges generative AI with user-generated content, enabling users to build bots-often modeled after fictional or public personas-for others to engage with. It is also popular, with over 20 million monthly active users, and impactful, with recent headlines detailing significant issues with youth engagement on the site. Character.AI is thus of interest to study both substantively and conceptually. To this end, we present a descriptive overview of the site using a dataset of 2.1 million English-language prompts (or ``greetings'') for chatbots on the site, created by around 1 million users. Our work explores the prevalence of different fandoms on the site, broader tropes that persist across fandoms, and how dynamics of power intersect with gender within greetings. Overall, our findings illuminate an emerging form of online (para)social interaction that toes a unique and important intersection between generative AI and user-generated content.

Problem

• Analyzing public-facing chatbots on Character.AI platform
• Exploring fandoms and tropes in user-generated chatbot interactions
• Investigating power dynamics and gender in AI-driven social interactions

Innovation

• Large-scale analysis of public-facing chatbots
• User-generated content merged with generative AI
• Exploration of online parasocial interaction dynamics