Public emotions on Internet: In case of AIGC

TL;DR

This paper analyzes public sentiment towards AI-generated content on social media, revealing demographic influences and platform differences, and introduces a real-time tracking system for opinion dynamics.

Contribution

It presents a novel real-time sentiment tracking system and connects group dynamics theory with social media analysis of AIGC opinions.

Findings

Negative correlation between age, education, and positive sentiment on Douyin

Weibo more prone to rapid spread of extreme viewpoints

Insights for managing online opinion and targeted campaigns

Abstract

The proliferation of interactive AI like ChatGPT has fueled intense public discourse surrounding AI- generated content (AIGC). While some fear job displacement, others anticipate productivity gains. Social media provides a rich source of data reflecting public opinion, attitudes, and behaviors. By examining the factors influencing collective sentiment toward AIGC on various platforms, we can refine products, marketing, and AI models themselves. Our research utilized a novel system for real-time tracking and detailed visualization of public mood related to AIGC. This system enabled analysis of the dynamics shaping opinions on nine AIGC products across China's three leading social media sites. Our findings reveal a negative correlation between user demographics (age and education) and positive sentiment towards AIGC on Douyin, contrasting with Weibo's susceptibility to the rapid spread of extreme viewpoints. This work uniquely connects group dynamics theory with social media sentiment, offering valuable guidance for managing online opinion and tailoring targeted campaigns.