  We consider the community detection problem in sparse random hypergraphs.
Angelini et al. (2015) conjectured the existence of a sharp threshold on model
parameters for community detection in sparse hypergraphs generated by a
hypergraph stochastic block model. We solve the positive part of the conjecture
for the case of two blocks: above the threshold, there is a spectral algorithm
which asymptotically almost surely constructs a partition of the hypergraph
correlated with the true partition. Our method is a generalization to random
hypergraphs of the method developed by Massouli\'{e} (2014) for sparse random
graphs.
