||While most social network research focuses on positive relational ties, such as friendship and information exchange, scholars are beginning to examine the dark side of human interaction, where negative connections represent different forms of interpersonal conflict, intolerance, and abuse. Despite this recent work, the extent to which positive and negative social networks differ remains unclear. The current project considers whether small-scale, structural network components can distinguish positive versus negative links. Using exponential random graph models (ERGMs), we examine these differences across various networks that include both positive and negative connections, such as ties of like versus dislike in groups of adults, friendship versus aggression among adolescents, and agreements versus disputes in online interaction. We find that both positive and negative networks contain more reciprocated dyads than expected by random chance. This tendency towards mutuality is especially pronounced in networks of positive interaction. At the same time, patterns of transitivity (i.e., if i is tied to j and j is tied to k, then i is tied to k) define positive but not negative graphs. Given the unique structural signatures of many negative networks, our results highlight the need for further theoretical and empirical research on the patterns of harmful interaction.