  In digital goods auctions, there is an auctioneer who sells an item with
unlimited supply to a set of potential buyers, and the objective is to design
truthful auction to maximize the total profit of the auctioneer. Motivated from
an observation that the values of buyers for the item could be interconnected
through social networks, we study digital goods auctions with positive
externalities among the buyers. This defines a multi-parameter auction design
problem where the private valuation of every buyer is a function of other
winning buyers. The main contribution of this paper is a truthful competitive
mechanism for subadditive valuations. Our competitive result is with respect to
a new solution benchmark $\mathcal{F}^{(3)}$; on the other hand, we show a
surprising impossibility result if comparing to the benchmark
$\mathcal{F}^{(2)}$, where the latter has been used quite successfully in
digital goods auctions without extenalities \cite{Goldberg2006}. Our results
from $\mathcal{F}^{(2)}$ to $\mathcal{F}^{(3)}$ could be considered as the loss
of optimal profit at the cost of externalities.
