# Understanding Public Perceptions of AI Conversational Agents: A Cross-Cultural Analysis

arXiv: https://arxiv.org/abs/2402.16039 · HTML: https://mlsanity.com/paper/2402.16039/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 119 references that are in the map.
- First posted on arXiv 25 Feb 2024.

## Builds on (most cited first, 9 of 9)

- [BERTopic: Neural topic modeling with a class-based TF-IDF procedure](https://mlsanity.com/paper/2203.05794/) (2022)
- [The Design and Implementation of XiaoIce, an Empathetic Social Chatbot](https://mlsanity.com/paper/1812.08989/) (2018)
- [What Makes a Good Conversation? Challenges in Designing Truly Conversational Agents](https://mlsanity.com/paper/1901.06525/) (2019)
- [Long-Term Trends in the Public Perception of Artificial Intelligence](https://mlsanity.com/paper/1609.04904/) (2016)
- [Exciting, Useful, Worrying, Futuristic: Public Perception of Artificial Intelligence in 8 Countries](https://mlsanity.com/paper/2001.00081/) (2019)
- [Alexa, Google, Siri: What are Your Pronouns? Gender and Anthropomorphism in the Design and Perception of Conversational Assistants](https://mlsanity.com/paper/2106.02578/) (2021)
- [Are Deepfakes Concerning? Analyzing Conversations of Deepfakes on Reddit and Exploring Societal Implications](https://mlsanity.com/paper/2203.15044/) (2022)
- [The Effect of Moderation on Online Mental Health Conversations](https://mlsanity.com/paper/2005.09225/) (2020)
- [Mapping Perceptions of Humanness in Speech-Based Intelligent Personal Assistant Interaction](https://mlsanity.com/paper/1907.11585/) (2019)

## Built on by (most cited first, 7 of 7)

- [AI Suggestions Homogenize Writing Toward Western Styles and Diminish Cultural Nuances](https://mlsanity.com/paper/2409.11360/) (2024)
- [Deconstructing Depression Stigma: Integrating AI-driven Data Collection and Analysis with Causal Knowledge Graphs](https://mlsanity.com/paper/2502.06075/) (2025)
- [Beyond PII: How Users Attempt to Estimate and Mitigate Implicit LLM Inference](https://mlsanity.com/paper/2509.12152/) (2025)
- [What if AI systems weren't chatbots?](https://mlsanity.com/paper/2605.07896/) (2026)
- [Esports Debut as a Medal Event at 2023 Asian Games: Exploring Public Perceptions with BERTopic and GPT-4 Topic Fine-Tuning](https://mlsanity.com/paper/2409.18798/) (2024)
- [MindfulAgents: Personalizing Mindfulness Meditation via an Expert-Aligned Multi-Agent System](https://mlsanity.com/paper/2603.06926/) (2026)
- [InnerPond: Fostering Inter-Self Dialogue with a Multi-Agent Approach for Introspection](https://mlsanity.com/paper/2603.27563/) (2026)

## Abstract (arXiv)

Conversational Agents (CAs) have increasingly been integrated into everyday life, sparking significant discussions on social media. While previous research has examined public perceptions of AI in general, there is a notable lack in research focused on CAs, with fewer investigations into cultural variations in CA perceptions. To address this gap, this study used computational methods to analyze about one million social media discussions surrounding CAs and compared people's discourses and perceptions of CAs in the US and China. We find Chinese participants tended to view CAs hedonically, perceived voice-based and physically embodied CAs as warmer and more competent, and generally expressed positive emotions. In contrast, US participants saw CAs more functionally, with an ambivalent attitude. Warm perception was a key driver of positive emotions toward CAs in both countries. We discussed practical implications for designing contextually sensitive and user-centric CAs to resonate with various users' preferences and needs.