1. A computer-implemented method comprising: receiving, by one or more computer systems, first information from a first type of channel and second information from a second type of channel, with the first type of channel differing from the second type of channel; merging the first information received from the first type of channel with the second information received from the second type of channel that differs from the first type of channel; applying an unsupervised clustering model to the merged information; and generating, based on results of the applying, a cross-channel cluster, the cross-channel cluster comprising (i) a portion of the first information received from the first type of channel associated with a subject matter, and (ii) a portion of the second information received from the second type of channel that differs from the first type of channel associated with the subject matter, wherein the cross-channel cluster comprises a cluster of information that is received from at least two different types of channels.