Many social outcomes emerge from relations rather than isolated individuals. Friendship, trade, coauthorship, organizational interdependence, and online interaction all create network structures that affect diffusion, influence, segregation, resilience, and inequality.

Network data are difficult because influence and selection are often entangled. People may become similar because they influence each other, because they choose similar peers, or because both are shaped by common environments. Untangling these processes is one of the field's most active methodological challenges.

Cutting-edge work combines temporal network models, diffusion on multiplex networks, causal inference on graphs, and computational simulation of complex systems. Social science increasingly studies how local interactions generate macro patterns such as polarization, institutional change, and collective action.