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.
ACM CHI Conference on Human Factors in Computing Systems