  The impacts of link recommendations on social networks are challenging to
evaluate, and so far they have been studied in limited settings. Observational
studies are restricted in the kinds of causal questions they can answer and
naive A/B tests often lead to biased evaluations due to unaccounted network
interference. Furthermore, evaluations in simulation settings are often limited
to static network models that do not take into account the potential feedback
loops between link recommendation and organic network evolution. To this end,
we study the impacts of recommendations on social networks in dynamic settings.
Adopting a simulation-based approach, we consider an explicit dynamic formation
model -- an extension of the celebrated Jackson-Rogers model -- and investigate
how link recommendations affect network evolution over time. Empirically, we
find that link recommendations have surprising delayed and indirect effects on
the structural properties of networks. Specifically, we find that link
recommendations can exhibit considerably different impacts in the immediate
term and in the long term. For instance, we observe that friend-of-friend
recommendations can have an immediate effect in decreasing degree inequality,
but in the long term, they can make the degree distribution substantially more
unequal. Moreover, we show that the effects of recommendations can persist in
networks, in part due to their indirect impacts on natural dynamics even after
recommendations are turned off. We show that, in counterfactual simulations,
removing the indirect effects of link recommendations can make the network
trend faster toward what it would have been under natural growth dynamics.
