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In this paper, we present the identification of five previously unknown giantradio galaxies (GRGs) using Data Release 1 of the Radio Galaxy Zoo citizenscience project and a selection method appropriate to the training andvalidation of deep learning algorithms for new radio surveys. We associate oneof these new GRGs with the brightest cluster galaxy (BCG) in the galaxy clusterGMBCG J251.67741+36.45295 and use literature data to identify a further 13previously known GRGs as BCG candidates, increasing the number of known BCGGRGs by >60%. By examining local galaxy number densities for the number of allknown BCG GRGs, we suggest that the existence of this growing number impliesthat GRGs are able to reside in the centers of rich ($\sim 10^{14}$M$_{\odot}$) galaxy clusters and challenges the hypothesis that GRGs grow tosuch sizes only in locally under-dense environments.

Radio Galaxy Zoo: New Giant Radio Galaxies in the RGZ DR1catalogue