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Cat Mai

dblp:283/4940 · DBLP profile ↗
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4ranked-venue papers
1as first author
4since 2021 · last 2026
0009-0002-8686-4725ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 3 · 3 since 2021Security and privacy · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
2 papers
Human-AI interaction · 51% Collaborative and social computing · 41% Health and well-being technologies · 8%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-AI interaction › conversational agents
chatbot interaction
1.012026
Caught in a Mafia Romance: How Users Explore Intimate Narratives with Chatbots · CHI 2026
Collaborative and social computing › social media › media sharing
social video sharing
0.512021
#StayHome #WithMe: How Do YouTubers Help with COVID-19 Loneliness? · CHI 2021
Collaborative and social computing › online communities
online community analysis
0.312026
Caught in a Mafia Romance: How Users Explore Intimate Narratives with Chatbots · CHI 2026
Health and well-being technologies › mental health
mental well-being
0.112021
#StayHome #WithMe: How Do YouTubers Help with COVID-19 Loneliness? · CHI 2021

Methods — techniques the papers use, named apart from their topics

reddit post analysis · 1.0empirical study · 1.0content analysis · 0.5
YearPublicationVenuePosition
2026 Caught in a Mafia Romance: How Users Explore Intimate Narratives with Chatbots
abstract
AI chatbots, built using large language models, are increasingly integrated into society and mimic the patterns of human text exchanges. While previous research has raised concerns that humans may form romantic attachment to chatbots, the range of AI-mediated interactions that people wish to create for themselves or others with chatbots remains poorly understood, particularly given the fast evolving landscape of chatbots. We provide an empirical study of Character.AI (cAI), a popular chatbot platform that enables users to design and share character-based bots, and synthesize this with an analysis of Reddit posts from cAI users. Contrary to popular narratives, we identify that users want to: (1) engage in intimate role-play with young adult, masculine-presenting characters that place users in a position of inferior power in well-defined scenarios and (2) immerse themselves in boundless, fantasy settings. We further find that users problematize both the excessive and insufficient sexualized content in such interactions which warrants novel digital-safety features.
Julia B. Kieserman, Cat Mai, Sara Lignell, Lucy Qin, Athanasios Andreou, Damon McCoy, Rosanna Bellini
CHI2
2025 More and Scammier Ads: The Perils of YouTube's Ad Privacy Settings
abstract
When users disable online ad personalization, they might be anticipating to see fewer ads that are "relevant" to them as a trade-off for more privacy. In this paper, we show that the tradeoff can go much further than this intuition. We conducted controlled experiments on YouTube in Australia, Canada, Ireland, the United Kingdom, and the United States to investigate the impact of disabling ad personalization on the quantity and quality of ads that users receive. Through experiments where emulated users with different ad privacy settings watched sequences of 400 videos, we show that disabling ad personalization can lead to the user being shown as much as 1.30 times more pre-roll ads than the default (least private) setting. More concerning is that in our experiments, the proportion of predatory ads increased 2.69 times compared to the default setting, from 2.5% to 8.7% of ads. This result highlights that certain user demographics (in this case, privacy-conscious users) can be exposed to significantly higher rates of predatory ads, and suggests that the platform's efforts to curb such ads are still falling short.
Cat Mai, Bruno Coelho, Julia B. Kieserman, Lexie Matsumoto, Kyle Spinelli, Eric Yang, Athanasios Andreou, Rachel Greenstadt, Tobias Lauinger, Damon McCoy
Proc. Priv. Enhancing Technol.1
2021 #StayHome #WithMe: How Do YouTubers Help with COVID-19 Loneliness?
abstract
Loneliness threatens public mental wellbeing during COVID-19. In response, YouTube creators participated in the #StayHome #WithMe movement (SHWM) and made myriad videos for people experiencing loneliness or boredom at home. User-shared videos generate parasocial attachment and virtual connectedness. However, there is limited knowledge of how creators contributed videos during disasters to provide social provisions as disaster-relief. Grounded on Weiss’s loneliness theory, this work analyzed 1488 SHWM videos to examine video sharing as a pathway to social provisions. Findings suggested that skill and knowledge sharing, entertaining arts, homelife activities, live chatting, and gameplay were the most popular video styles. YouTubers utilized parasocial relationships to form a space for staying away from the disaster. SHWM YouTubers provided friend-like, mentor-like, and family-like provisions through videos in different styles. Family-like provisions led to the highest overall viewer engagement. Based on the findings, design implications for supporting viewers’ mental wellbeing in disasters are discussed.
Shuo Niu, Ava Bartolome, Cat Mai, Nguyen Binh Ha
CHI3
2021 #TeamTrees: Investigating How YouTubers Participate in a Social Media Campaign
abstract
YouTube is not only a platform for content creators to share videos but also a virtual venue for hosting community activities, such as social media campaigns (SMCs). SMCs for public awareness is a growing and reoccurring phenomenon on YouTube, during which content creators make videos to engage their audience and raise awareness of global challenges. However, how the unique celebrity culture on YouTube affects collective actions is an underexplored area. This work examines an SMC on YouTube, #TeamTrees, initiated by a YouTube celebrity and sought to raise people's awareness of tree-planting and climate change. The authors annotated and analyzed 992 #TeamTrees videos to explore how YouTube celebrities, professionals, and amateurs in different channel topics diagnose problems, present solutions, and motivate actions. This study also looks into whether platform identities and framing activities affect campaign reach and engagement. Results suggest that #TeamTrees reached creators who are generally not active in social issues. The participating YouTubers were likely to motivate the viewers to donate and join celebrities' and community's actions, but less involved in examining the environmental problems. Celebrities' videos dominated the campaign's influence. Amateurs' videos had a higher engagement level, although they need more support to frame campaign activities. Based on these findings, we discuss design implications for video-sharing platforms to support future SMCs.
Shuo Niu, Cat Mai, Katherine G. McKim, D. Scott McCrickard
Proc. ACM Hum. Comput. Interact.2