A large amount of research finds associations between individuals' attributes and the position of individuals in network structures. In this article, I illustrate how such associations systematically affect the assessment of attributes through network neighbors. The friendship paradox-a general regularity in network contexts, which states that your friends are likely to have more friends than you-becomes relevant and extends to individuals' attributes as well. First, I show that your friends are likely to be better informed (closeness), better intermediaries (betweenness) and more powerful (eigenvector) than you. Second, I suggest more generally that your friends are likely to be more special in their attributes than the population at large. Finally, I investigate the implications of this phenomenon in a dynamic setting. Applying calibrated agent-based simulations, I use a model of attribute adoption to emphasize how structurally introduced experiences penetrate the trajectory of social processes. Existing research does not yet adequately acknowledge this phenomenon.