||Network motifs represent local subgraphs, such as dyads, triads, and tetrads, that occur repeatedly. Biology, physical sciences, social and economic sciences, and other network science disciplines, document multiple instances in which motifs appear in graphs that provide insight into the structure and processes of these networks. We focus on social networks and examine the prevalence of dyad, triad, and symmetric tetrad motifs among six types of social interactions: friendship, legislative cosponsorship, Twitter messages, advice seeking, email communication, and terrorist collusion. Here, we use four networks of each type, for a total sample of 24 social networks. We find important commonalities across the six types of networks and document five motifs that arise when comparing our observed networks to random graphs generated using the U|MAN null distribution (one dyad, three triads, and one symmetric tetrad). Results support our hypotheses regarding high levels of clustering and transitivity. With some exceptions, the six different types of graphs also tend to develop their own “network signatures,” based on triad and tetrad patterns. Our findings demonstrate the utility of examining local structural subgraphs in social networks, with implications for social theory and links to other scientific disciplines.