Support-seekers' active engagement with received comments, e.g., showing positive sentiment and willingness to improve in the replies, can indicate the success of online health communities (OHCs). Their participation in other communities may correlate with their engagement in OHCs but remains under-explored. This paper analyzes 26, 725 seekers' behaviors in the other 40, 479 communities and their associations with seekers' engagement with received comments under their 78, 501 posts in 30 Baidu Tieba OHCs. We found that seekers primarily posted in other communities that are also health-related (25.3%), followed by those about games and entertainment (e.g., Dota, 20.8%). Seekers who posted in other communities about health (26.3%) or personal issues (e.g., saving money, 20.7%) before had relatively higher probabilities of subsequently posting in the 30 OHCs we identified, but this posting experience was associated with fewer replies and less expressed willingness to improve based on received comments. We provide insights into fostering seekers' engagement in OHCs based on cross-community interactions.
Group conversations are a fundamental yet complex form of social interaction central to human cognition and telecommunication technology. While understanding and facilitating these interactions has been a long-standing goal, findings are often isolated within specific in-person o…
This paper is an extension of a paper presented at the ICAART 2026 conference, which introduced LEA (Learning Engagement Assistant), an adaptive AI tutoring agent combining course-specific Retrieval-Augmented Generation (RAG) with structured Knowledge Component (KC) models across…
Background: Conversational AI chatbots designed for mental health may offer an accessible, scalable avenue for supporting psychological well-being, yet prior evaluations have largely focused on clinical symptom reduction rather than broader indicators of day-to-day functioning, a…
Large language model personas are increasingly used to approximate diverse users during early-stage visualization design, but it remains unclear whether persona-conditioned outputs reflect stable personality effects or artifacts of model choice and task framing. We examine this q…
As LLMs become increasingly capable of completing tasks for users, a central concern is that everyday AI use may become primarily cognitive offloading, eroding the opportunities through which people develop their own capabilities. We analyse large-scale human--LLM conversations t…
User experience (UX) designers face barriers when creating data visualizations due to limited domain expertise in visualization or unfamiliarity with specialized tools. This highlights a clear need for effective methods to build visualization literacy. To address this, we evaluat…