Stance Signaling for Social Justice on Social Media: Does It Boost and Accelerate User Engagement?

Abstract

Social media platforms increasingly serve as spaces for engaging with complex and socially sensitive topics. However, users’ willingness to interact with such content is often shaped not only by the content itself but also by the design of interaction mechanisms. This study investigates how alternative interface designs with embedded stance-signaling mechanisms affect user engagement, decision-making, and attention compared to the traditional interface. We proposed two stance-signaling techniques that allow users to anonymously express their stance on a social justice post before the aggregated vote results are shown. Using a controlled experiment with 1,080 observations from 90 participants, we employed a generalized mixed model (GMM) and a Linear Mixed Model (LMM) alongside eye-tracking measures to examine interaction behavior, response time, and visual attention. Results indicate that while post type, whether positive (supportive) or negative (hostile), influences engagement in traditional interfaces, its effect is substantially reduced in alternative designs that also incorporate stance-signaling. Additionally, these stance-signaling mechanisms lead to more reactions than skips and to faster decision-making, suggesting reduced cognitive and social barriers to participation. These findings highlight the importance of interface affordances in shaping online behavior and suggest that alternative interaction designs can promote more inclusive and consistent engagement, particularly in contexts involving socially sensitive content.