Understanding the Impact of AI-Generated Content on Social Media: The Pixiv Case

Yiluo Wei, Gareth Tyson

Abstract: In the last two years, Artificial Intelligence Generated Content (AIGC) has received significant attention, leading to an anecdotal rise in the amount of AIGC being shared via social media platforms. The impact of AIGC and its implications are of key importance to social platforms, e.g., regarding the implementation of policies, community formation, and algorithmic design. Yet, to date, we know little about how the arrival of AIGC has impacted the social media ecosystem. To fill this gap, we present a comprehensive study of Pixiv, an online community for artists who wish to share and receive feedback on their illustrations. Pixiv hosts over 100 million artistic submissions and receives more than 1 billion page views per month (as of 2023). Importantly, it allows both human and AI generated content to be uploaded. Exploiting this, we perform the first analysis of the impact that AIGC has had on the social media ecosystem, through the lens of Pixiv. Based on a dataset of 15.2 million posts (including 2.4 million AI-generated images), we measure the impact of AIGC on the Pixiv community, as well as the differences between AIGC and human-generated content in terms of content creation and consumption patterns. Our results offer key insight to how AIGC is changing the dynamics of social media platforms like Pixiv.

Primary Subject Area: [Generation] Social Aspects of Generative AI

Secondary Subject Area: [Experience] Art and Culture

Relevance To Conference:

This paper is directly relevant to the theme of "social aspects of generative AI", providing an empirical investigation into the impact of AI-generated content on Pixiv, an online social media platform.
Our results offer key insight to how AI-generated content is changing the dynamics of social media platforms. This understanding assists these platforms in more effectively fostering fairness, transparency, and an improved user experience in the Generative AI Era.

Submission Number: 1303