activity
20242026
most citedPrivacy as Social Norm: Systematically Reducing Dysfunctional Privacy Concerns on Social Media

7 citations · 7 across the 6 of their papers we have counts for

collaborators

6 papers

cs.HC2026

Assessing the Applicability of Existing Design Recommendations to AI Companion Design: A Multi-Method Study

Soobin Cho, Deveshi Modi, Divya Mavinkurve +2

With the rapid proliferation of large language model (LLM)-based systems, AI companions have emerged as conversational agents designed to cultivate emotional connection rather than…

cs.HC2026

Delegating Before Learning: Where Generative AI Sits in Students' Professional Communication

Jared Ren, Soobin Cho

We conducted an interview study with twelve students on their use of generative AI in academic communication. Students delegated professional messages to AI most where the pressure…

cs.HC2026

How Much Can AI Understand? Toward AI-Assisted Sensemaking of Collaborative Discussion in Groups with Shared History

Soobin Cho, Mark Zachry, David W. McDonald

AI tools that support collaborative discussion typically treat the discussion as a standalone task, focusing only on its content and setting aside the social context of the group h…

cs.HC2025

A Framework for AI-Supported Mediation in Community-based Online Collaboration

Soobin Cho, Mark Zachry, David W. McDonald

Online spaces involve diverse communities engaging in various forms of collaboration, which naturally give rise to discussions, some of which inevitably escalate into conflict or d…

cs.HC2025

LLMs in Wikipedia: Investigating How LLMs Impact Participation in Knowledge Communities

Moyan Zhou, Soobin Cho, Loren Terveen

Large language models (LLMs) are reshaping knowledge production as community members increasingly incorporate them into their contribution workflows. However, participating in know…

cs.HC2024★ 7 cited

Privacy as Social Norm: Systematically Reducing Dysfunctional Privacy Concerns on Social Media

JaeWon Kim, Soobin Cho, Robert Wolfe +2

Through co-design interviews () and a design evaluation survey (N=136) with U.S. teens ages 13-18, we investigated teens' privacy management on social media. Our study reveal…