Significance Polarization is rising while political debates are moving to online social platforms. In such settings, algorithms are used to recommend new connections to users, through so-called link recommendation algorithms. Users are often recommended based on structural similarity (e.g., nodes sharing many neighbors are similar). We show that preferentially establishing links with structurally similar nodes potentiates opinion polarization by stimulating network topologies with well-defined communities (even in the absence of opinion-based rewiring). When networks are composed of nodes that react differently to out-group contacts—either converging or polarizing—connecting structurally dissimilar nodes enhances moderate opinions. Our study sheds light on the impacts of social-network algorithms in opinion dynamics and unveils avenues to steer polarization in online social networks.