Seunghyun Kim

schoolGeorgia Institute of Technologybar_chart#2597 Global Rank

Total Papers

HCI Rank

#2597

Research Areas

Years Active

Recent Publications

Getting Meta: A Multimodal Approach for Detecting Unsafe Conversations within Instagram Direct Messages of Youth

Instagram, one of the most popular social media platforms among youth, has recently come under scrutiny for potentially being harmful to the safety and well-being of our younger generations. Automated approaches for risk detection may be one way to help mitigate some of these risks if such algorithms are both accurate…

CSCW '232nd AuthorSafety

Sliding into My DMs: Detecting Uncomfortable or Unsafe Sexual Risk Experiences within Instagram Direct Messages Grounded in the Perspective of Youth

We collected Instagram data from 150 adolescents (ages 13-21) that included 15,547 private message conversations of which 326 conversations were flagged as sexually risky by participants. Based on this data, we leveraged a human-centered machine learning approach to create sexual risk detection classifiers for youth s…

CHI '223rd AuthorHonorable MentionOnline Harassment & Counter-Tools +2

Understanding the Digital Lives of Youth: Analyzing Media Shared within Safe Versus Unsafe Private Conversations on Instagram

We collected Instagram Direct Messages (DMs) from 100 adolescents and young adults (ages 13-21) who then flagged their own conversations as safe or unsafe. We performed a mixed-method analysis of the media files shared privately in these conversations to gain human-centered insights into the risky interactions experie…

CSCW '212nd AuthorAlgorithmic Auditing and Responsible AI

A Human-Centered Systematic Literature Review of the Computational Approaches for Online Sexual Risk Detection

In the era of big data and artificial intelligence, online risk detection has become a popular research topic. From detecting online harassment to the sexual predation of youth, the state-of-the-art in computational risk detection has the potential to protect particularly vulnerable populations from online victimizati…

CSCW '211st AuthorAntisocial Computing

A Human-Centered Systematic Literature Review of Cyberbullying Detection Algorithms

Cyberbullying is a growing problem across social media platforms, inflicting short and long-lasting effects on victims. As such, research has looked into building automated systems, powered by machine learning, to detect cyberbullying incidents, or the involved actors like victims and perpetrators. In the past, system…

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