Digital empathy study wins recognition at CHI 2026
In a new article about online empathy, the authors propose a multidimensional, relational, and contextualized approach.
In a new article about online empathy, the authors propose a multidimensional, relational, and contextualized approach.
At Meedan, we’re pleased to announce that a paper we co-authored on empathy practices in social media discourse received an honorable mention at the 2026 ACM Conference on Human Factors in Computing Systems (CHI 2026). CHI is regarded as one of the most respected annual gatherings in computer science, and less than 5% of the papers submitted to the conference received an honorable mention or best paper award. The paper was authored by Meedan Director of Research Scott A. Hale and Yixin Chen and Bernie Hogan of the Oxford Internet Institute, where Hale also serves as the director.
In our everyday lives, we offer and accept empathy in a variety of ways. During a conversation with a loved one about their day, we might take a moment to put their story into our own words. We may shake our heads in dismay to show we share in their frustration as they tell us about something upsetting. But when we go out to see an emotionally poignant movie, we probably wouldn’t turn around to tell a misty-eyed fellow audience member that we know just how they feel while the picture is still rolling.
Online, many of these same tenets still hold. Asking a forum populated by new parents for a straightforward recommendation of a budget-friendly car seat encourages a different kind and type of response compared to sharing about a recent diagnosis in a digital cancer support group. Chen, Hogan, and Hale contend that our currently limited binary understanding of online empathy needs to be expanded.
“Rather than treating empathy as inherently positive, we argue platform designers and community leaders need to consider context and should seek to elicit empathy from their users judiciously,” the authors write.
Empathy is widely regarded as inherently positive in supportive online interactions, but its value is shaped by context. This study argues that empathy should be understood not as a uniform good but as a multidimensional, relational practice. Rather than treating empathy as binary, we propose a framework that captures how empathy is solicited in posts and expressed in replies, emphasising that context is critical in determining its appropriateness and effectiveness. Using post-reply data from six Reddit and Stack Exchange communities, we conduct a three-phase study. First, we develop a fine-grained annotation framework to capture distinct empathy practices in both posts and replies. Second, we fine-tune language models to detect these nuanced practices. Third, we apply the models at scale and examine platform- and community-specific patterns of empathy elicitation and expression. Our findings challenge current assumptions about online empathy and offer a more contextualised understanding of its role in online discourse. We identify future directions for platform design and contextual community support.
We extend congratulations to Yixin Chen, Bernie Hogan, and Scott A. Hale for their important and timely contributions toward better understanding the intersections of empathy and our digital lives.
