  The widespread online misinformation could cause public panic and serious
economic damages. The misinformation containment problem aims at limiting the
spread of misinformation in online social networks by launching competing
campaigns. Motivated by realistic scenarios, we present the first analysis of
the misinformation containment problem for the case when an arbitrary number of
cascades are allowed. This paper makes four contributions. First, we provide a
formal model for multi-cascade diffusion and introduce an important concept
called as cascade priority. Second, we show that the misinformation containment
problem cannot be approximated within a factor of
$\Omega(2^{\log^{1-\epsilon}n^4})$ in polynomial time unless $NP \subseteq
DTIME(n^{\polylog{n}})$. Third, we introduce several types of cascade priority
that are frequently seen in real social networks. Finally, we design novel
algorithms for solving the misinformation containment problem. The
effectiveness of the proposed algorithm is supported by encouraging
experimental results.
