  One of the important yet insufficiently studied subjects in fair allocation
is the externality effect among agents. For a resource allocation problem,
externalities imply that a bundle allocated to an agent may affect the
utilities of other agents.
  In this paper, we conduct a study of fair allocation of indivisible goods
when the externalities are not negligible. We present a simple and natural
model, namely \emph{network externalities}, to capture the externalities. To
evaluate fairness in the network externalities model, we generalize the idea
behind the notion of maximin-share ($\MMS$) to achieve a new criterion, namely,
\emph{extended-maximin-share} ($\EMMS$). Next, we consider two problems
concerning our model.
  First, we discuss the computational aspects of finding the value of $\EMMS$
for every agent. For this, we introduce a generalized form of partitioning
problem that includes many famous partitioning problems such as maximin,
minimax, and leximin partitioning problems. We show that a $1/2$-approximation
algorithm exists for this partitioning problem.
  Next, we investigate on finding approximately optimal $\EMMS$ allocations.
That is, allocations that guarantee every agent a utility of at least a
fraction of his extended-maximin-share. We show that under a natural assumption
that the agents are $\alpha$-self-reliant, an $\alpha/2$-$\EMMS$ allocation
always exists. The combination of this with the former result yields a
polynomial-time $\alpha/4$-$\EMMS$ allocation algorithm.
