# Excitements and Concerns in the Post-ChatGPT Era: Deciphering Public Perception of AI through Social Media Analysis

arXiv: https://arxiv.org/abs/2307.05809 · HTML: https://mlsanity.com/paper/2307.05809/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Jul 2023.

## Built on by (most cited first, 4 of 4)

- [Representation Bias in Political Sample Simulations with Large Language Models](https://mlsanity.com/paper/2407.11409/) (2024)
- [Understanding Risk and Dependency in AI Chatbot Use from User Discourse](https://mlsanity.com/paper/2602.09339/) (2026)
- [Understanding Divergent Framing of the Supreme Court Controversies: Social Media vs. News Outlets](https://mlsanity.com/paper/2309.09508/) (2023)
- [Trust, Experience, and Innovation: Key Factors Shaping American Attitudes About AI](https://mlsanity.com/paper/2503.05815/) (2025)

## Abstract (arXiv)

As AI systems become increasingly prevalent in various aspects of daily life, gaining a comprehensive understanding of public perception towards these AI systems has become increasingly essential for several reasons such as ethical considerations, user experience, fear, disinformation, regulation, collaboration, and co-creation. In this study, we investigate how mass social media users perceive the recent rise of AI frameworks such as ChatGPT. We collect a total of 33,912 comments in 388 unique subreddits spanning from November 30, 2022 to June 8, 2023 using a list of AI-related keywords. We employ BERTopic to uncover the major themes regarding AI on Reddit. Additionally, we seek to gain deeper insights into public opinion by examining the distribution of topics across different subreddits. We observe that technology-related subreddits predominantly focus on the technical aspects of AI models. On the other hand, non-tech subreddits show greater interest in social issues such as concerns about job replacement or furlough. We leverage zero-shot prompting to analyze the sentiment and perception of AI among individual users. Through a comprehensive sentiment and emotion analysis, we discover that tech-centric communities exhibit greater polarization compared to non-tech communities when discussing AI topics. This research contributes to our broader understanding of public opinion surrounding artificial intelligence.