GPT Store Mining and Analysis

TL;DR

This paper conducts a comprehensive measurement study of the GPT Store, analyzing GPT categorization, factors influencing popularity, and security risks to inform future AI ecosystem development.

Contribution

It provides the first detailed analysis of GPT Store organization, user preferences, and security vulnerabilities, offering insights into its operational dynamics.

Findings

GPTs are categorized effectively by topic.

User preferences significantly influence GPT popularity.

Security risks include potential threats and vulnerabilities.

Abstract

As a pivotal extension of the renowned ChatGPT, the GPT Store serves as a dynamic marketplace for various Generative Pre-trained Transformer (GPT) models, shaping the frontier of conversational AI. This paper presents an in-depth measurement study of the GPT Store, with a focus on the categorization of GPTs by topic, factors influencing GPT popularity, and the potential security risks. Our investigation starts with assessing the categorization of GPTs in the GPT Store, analyzing how they are organized by topics, and evaluating the effectiveness of the classification system. We then examine the factors that affect the popularity of specific GPTs, looking into user preferences, algorithmic influences, and market trends. Finally, the study delves into the security risks of the GPT Store, identifying potential threats and evaluating the robustness of existing security measures. This study offers a detailed overview of the GPT Store's current state, shedding light on its operational dynamics and user interaction patterns. Our findings aim to enhance understanding of the GPT ecosystem, providing valuable insights for future research, development, and policy-making in generative AI.