Capturing Diverse and Precise Reactions to a Comment with User-Generated Labels

Simple up/downvotes, arguably the most widely used reaction design across social media platforms, allow users to efficiently express their opinions and quickly evaluate others' opinions from aggregated votes. However, such design forces users to project their diverse opinions onto dichotomized reactions and provides limited information to readers on why a comment was up/downvoted. We explore user-generated labels (UGLs) as an alternative reaction design to capture the rich context of user reactions to comments. We conducted a between-subjects study with 218 participants to understand how people use and are influenced by UGLs compared to up/downvotes. Specifically, we examine how UGLs affect users' ability to express and perceive diverse opinions. Participants generated 234 unique labels on diverse aspects of a comment. Leaving more reactions than participants in the up/downvotes condition, participants reported that the ability to express their opinions improved with UGLs. UGLs also enabled participants to better understand the multifacetedness of public evaluation of a comment. CCS CONCEPTS • Human-centered computing → Empirical studies in collaborative and social computing; Social media.