  Social networks have well documented effects at the individual and aggregate
level. Consequently it is often useful to understand how an attempt to
influence a network will change its structure and consequently achieve other
goals. We develop a framework for network modification that allows for
arbitrary objective functions, types of modification (e.g. edge weight
addition, edge weight removal, node removal, and covariate value change), and
recovery mechanisms (i.e. how a network responds to interventions). The
framework outlined in this paper helps both to situate the existing work on
network interventions but also opens up many new possibilities for intervening
in networks. In particular use two case studies to highlight the potential
impact of empirically calibrating the objective function and network recovery
mechanisms as well as showing how interventions beyond node removal can be
optimised. First, we simulate an optimal removal of nodes from the Noordin
terrorist network in order to reduce the expected number of attacks (based on
empirically predicting the terrorist collaboration network from multiple types
of network ties). Second, we simulate optimally strengthening ties within
entrepreneurial ecosystems in six developing countries. In both cases we
estimate ERGM models to simulate how a network will endogenously evolve after
intervention.
