Last Week with ChatGPT: A Weibo Study on Social Perspective Regarding ChatGPT for Education and Beyond

TL;DR

This paper analyzes Chinese public sentiment toward ChatGPT in education and human–computer interaction using Sina Weibo data, comparing reactions before and after GPT-4. It employs XLM-RoBERTa-based three-category sentiment analysis, LDA topic modeling, and chi-square tests to quantify attitude shifts and extract concerns. Across three educational scenarios (exams, homework, originality) and three human-AI contexts, neutral sentiment dominates, but GPT-4 generally increases positive attitudes while reducing some negative views, with persistent worries about privacy, bias, and loss of originality. The findings inform a cautious, governance-minded approach to deploying AI tools in education and everyday life, highlighting areas for policy, pedagogy, and tool design to maximize benefits and mitigate risks.

Abstract

The application of AI-powered tools has piqued the interest of many fields, particularly in the academic community. This study uses ChatGPT, currently the most powerful and popular AI tool, as a representative example to analyze how the Chinese public perceives the potential of large language models (LLMs) for educational and general purposes. Although facing accessibility challenges, we found that the number of discussions on ChatGPT per month is 16 times that of Ernie Bot developed by Baidu, the most popular alternative product to ChatGPT in the mainland, making ChatGPT a more suitable subject for our analysis. The study also serves as the first effort to investigate the changes in public opinion as AI technologies become more advanced and intelligent. The analysis reveals that, upon first encounters with advanced AI that was not yet highly capable, some social media users believed that AI advancements would benefit education and society, while others feared that advanced AI, like ChatGPT, would make humans feel inferior and lead to problems such as cheating and a decline in moral principles. The majority of users remained neutral. Interestingly, with the rapid development and improvement of AI capabilities, public attitudes have tended to shift in a positive direction. We present a thorough analysis of the trending shift and a roadmap to ensure the ethical application of ChatGPT-like models in education and beyond.

Figures (10)

• Figure 1: The steps for obtaining and analyzing data.
• Figure 2: Sentiment analysis, the inner and outer circles indicate results before and after the release of GPT-4, respectively. (a) ChatGPT and Education. (b) Scenario 1: Examination and Cheating. (c) Scenario 2: Assisting with homework. (d) Scenario 3-Paper and Originality.
• Figure 3: Topic analysis, top-20 most salient terms of "ChatGPT and Education". (a) before the release. (b) after the release.
• Figure 4: Topic analysis, top-20 most salient terms of "Examinations and Cheating". (a) before the release. (b) after the release.
• Figure 5: Topic analysis, top-20 Most Salients Terms of "Assisting with homework". (a) Before the Release. (b) After the Release.