Social voting plays a key role in the organization of user-contributed content; readers are asked to indicate what they “like” or find “helpful,” with collected votes then used to prioritize valued content. Despite the popularity of these mechanisms, little is known as to how users employ and interpret this feedback. We conducted a study in which participants researched items at two review communities, keeping lists of reviews they found helpful and not. We observed their behaviors and asked them to rate reviews on several dimensions. We found consensus that helpful contributions are clearly written, relevant to users' needs, and express an appropriate amount of information. We also observed that users relied on others' judgments, attending to the most helpful content. We discuss implications, when users behave as though what is helpful to others is helpful to them.